diff --git a/ricks/rick.py b/ricks/rick.py
index 3cdc31d..1c00eb4 100644
--- a/ricks/rick.py
+++ b/ricks/rick.py
@@ -1,771 +1,771 @@
-# -*- coding: utf-8 -*-
-#!/usr/bin/env python
-"""
-Version 0.8.0 
-
-"""
-
-from psycopg2 import connect
-import psycopg2.sql as pg
-import pandas.io.sql as pandasql
-import matplotlib as mpl
-import matplotlib.pyplot as plt
-import matplotlib.patches as patches
-import matplotlib.ticker as ticker
-import matplotlib.font_manager as font_manager
-import geopandas as gpd
-import os
-import shapely
-import seaborn as sns
-from shapely.geometry import Point
-import numpy as np
-
-class font:
-    """
-    Class defining the global font variables for all functions.
-    
-    """
-    
-    leg_font = font_manager.FontProperties(family='Libre Franklin',size=9)
-    normal = 'Libre Franklin'
-    semibold = 'Libre Franklin SemiBold'
-    
-    
-class colour:
-    """
-    Class defining the global colour variables for all functions.
-    
-    """
-    purple = '#660159'
-    grey = '#7f7e7e'
-    light_grey = '#777777'
-    blue = '#253494'
-    orange = '#0D9F73'
-    cmap = 'YlOrRd'
-    
-class geo:
-    """
-    Class for additional gis layers needed for the cloropleth map.
-    
-    """
-
-    def ttc(con):
-        """Function to return the TTC subway layer.
-        
-        Parameters
-        ------------
-        con : SQL connection object
-            Connection object needed to connect to the RDS
-        
-        Returns
-        --------
-        gdf
-            Geopandas Dataframe of the Subway Layer
-        
-        """
-        query = '''SELECT * FROM gis.subway_to'''
-        
-        ttc = gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom')
-        ttc = ttc.to_crs('epsg:3857')
-        
-        for index, row in ttc.iterrows():
-            rotated = shapely.affinity.rotate(row['geom'], angle=-17, origin = Point(0, 0))
-            ttc.loc[index, 'geom'] = rotated  
-        
-        return ttc 
-    
-    def island(con):
-        
-        """Function to return a layer of the Toronto island. Since the island is classified in the same neighbourhood as the waterfront, in some cases its not completely accurate to show the island shares the same data as the waterfront. 
-        
-        Parameters
-        ------------
-        con : SQL connection object
-            Connection object needed to connect to the RDS
-        
-        Returns
-        --------
-        gdf
-            Geopandas Dataframe of the Toronto island.
-        
-        """
-        
-        query = '''
-
-        SELECT 
-        geom
-        FROM gis.zones_tts06
-        WHERE gta06 = 81
-
-        '''
-
-        island =  gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom')
-        island  = island.to_crs('epsg:3857')
-
-        for index, row in island.iterrows():
-            rotated = shapely.affinity.rotate(row['geom'], angle=-17, origin = Point(0, 0)) 
-            island.loc[index, 'geom'] = rotated
-
-        return island
-     
-    
-class charts:
-    """
-    Class defining all the charting functions.
-    
-    """
-    
-    global func
-    def func():
-        
-        """Function to set global settings for the charts class. 
-        
-        """
-        
-        sns.set(font_scale=1.5) 
-        mpl.rc('font',family='Libre Franklin')
-    
-    def chloro_map(con, df, subway, island, lower, upper, title, **kwargs):
-        """Creates a chloropleth map
-
-        Parameters
-        -----------
-        con : SQL connection object
-                Connection object needed to connect to the RDS
-        df : GeoPandas Dataframe
-                Data for the chloropleth map. The data must only contain 2 columns; the first column has to be the geom column and the second has to be the data that needs to be mapped.
-        lower : int
-                Lower bound for colourmap
-        upper : int
-                Upper bound for the colourmap
-        title : str
-                Legend label
-        cmap : str, optional, default: YlOrRd
-                Matplotlib colourmap to use for the map
-        unit : str, optional
-                Unit to append to the end of the legend tick
-        nbins : int, optional, defualt: 2
-                Number of ticks in the colourmap
-
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-
-        """ 
-
-        cmap = kwargs.get('cmap', colour.cmap)
-        unit = kwargs.get('unit', None)
-        nbins = kwargs.get('nbins', 2)
-
-        df.columns = ['geom', 'values']
-        light = '#d9d9d9'
-
-        fig, ax = plt.subplots(dpi=450.0)
-        fig.set_size_inches(6.69,3.345)
-
-        ax.set_yticklabels([])
-        ax.set_xticklabels([])
-        ax.set_axis_off()
-
-        mpd = df.plot(column='values', ax=ax, vmin=lower, vmax=upper,  cmap = cmap, edgecolor = 'w', linewidth = 0.5)
-
-
-        if subway == True:
-            ttc_df = geo.ttc(con)
-            line = ttc_df.plot( ax=ax, linewidth =4, color = 'w', alpha =0.6) # ttc subway layer
-            line = ttc_df.plot( ax=ax, linewidth =2, color = 'k', alpha =0.4) # ttc subway layer
-
-        if island == False:
-                island_grey = geo.island(con)
-                island_grey.plot(ax=ax, edgecolor = 'w', linewidth = 4,  color = light)
-                island_grey.plot(ax=ax, edgecolor = 'w', linewidth = 0,  color = light)
-
-
-        props = dict(boxstyle='round', facecolor='w', alpha=0)
-        plt.text(0.775, 0.37, title, transform=ax.transAxes, wrap = True, fontsize=7, fontname = font.semibold,
-                verticalalignment='bottom', bbox=props, fontweight = 'bold') # Adding the Legend Title
-
-
-        cax = fig.add_axes([0.718, 0.16, 0.01, 0.22]) # Size of colorbar
-
-        #rect = patches.Rectangle((0.76, 0.01),0.235,0.43,linewidth=0.5, transform=ax.transAxes, edgecolor=light,facecolor='none')
-        #ax.add_patch(rect)
-
-        ax.margins(0.1)
-
-        sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=lower, vmax=upper))
-        sm._A = []
-        cbr = fig.colorbar(sm, cax=cax)
-        cbr.outline.set_linewidth(0)
-        tick_locator = ticker.MaxNLocator(nbins=nbins)
-        cbr.locator = tick_locator
-        cbr.update_ticks()
-        cbr.ax.yaxis.set_tick_params(width=0.5)
-        cbr.ax.tick_params(labelsize=6)  # Formatting for Colorbar Text
-        for l in cbr.ax.yaxis.get_ticklabels():
-                l.set_family(font.normal)
-
-        if unit is not None:
-            if 0 < upper < 10:
-                ax.text(0.829, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left') 
-            elif 10 <= upper < 100:
-                ax.text(0.839, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
-            elif 100 <= upper < 1000:
-                ax.text(0.851, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
-            elif 1000 <= upper < 100000:
-                ax.text(0.862, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
-            else:
-                 pass
-
-        return fig, ax
-
-    def histogram_chart(data, ylab, xlab, nbin, **kwargs):
-        """Creates a histogram chart with specified nbin (nbin data)
-        
-        Parameters
-        -----------
-        data : array like or scalar
-            Data for the line chart.
-        ylab : str
-            Label for the y axis.
-        xlab : str
-            Label for the x axis.
-        ymax : int, optional, default is the max y value
-            The max value of the y axis
-        ymin : int, optional, default is 0
-            The minimum value of the y axis
-        
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-        props
-            Dictionary of the text annotation properties
-            
-        """
-        
-        func()
-        xmax = kwargs.get('xmax', None)
-        xmin = kwargs.get('xmin', 0)
-        
-        if (xmax is None):
-            xmax = int(max(data))
-        
-        if (nbin is None):
-            nbin = 10
-        
-        plt.style.use('seaborn-whitegrid')
-        fig, ax = plt.subplots(1,1, dpi=450.0)
-        fig.set_size_inches(6.1, 4.2)
-        ax.hist(data, bins=nbin, alpha=1.0, color=colour.purple)
-        ax.set_xlabel(xlab)
-        ax.set_ylabel(ylab)
-        ax.set_xlim(xmin, xmax)
-        ax.legend(loc='upper right')
-        
-        return fig, ax
-    
-        
-    def line_chart(data, ylab, xlab, **kwargs):
-        """Creates a line chart. x axis must be modified manually
-        
-        Parameters
-        -----------
-        data : array like or scalar
-            Data for the line chart.
-        ylab : str
-            Label for the y axis.
-        xlab : str
-            Label for the x axis.
-        xticker_labels : array, optional, with ticker identifications
-            Tickers for the x axis. 
-        ymax : int, optional, default is the max y value
-            The max value of the y axis
-        ymin : int, optional, default is 0
-            The minimum value of the y axis
-        baseline : array like or scalar, optional, default is None
-            Data for another line representing the baseline.
-        addedline1 : array like or scalar, optional, default is None
-            Data for another line representing the addedline1.
-        addedline2 : array like or scalar, optional, default is None
-            Data for another line representing the addedline2.
-        yinc : int, optional
-            The increment of ticks on the y axis.
-        list_legends: list, optional (when baseline is ON)
-            List of legend names to show on plot
-            
-       min_text : array of min-value text information, default is None
-       max_text : array of max-value text information, default is None
-           
-        
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-        props
-            Dictionary of the text annotation properties
-            
-        """
-        
-        func()
-        ymax = kwargs.get('ymax', int(data.max()))
-        ymin = kwargs.get('ymin', 0)
-        baseline = kwargs.get('baseline', None)
-        addedline1 = kwargs.get('addedline1', None)
-        addedline2 = kwargs.get('addedline2', None)
-        list_legends = kwargs.get('list_legends', None)
-        min_text     = kwargs.get('min_text', None)
-        max_text     = kwargs.get('max_text', None)
-        xticker_labels = kwargs.get('xticker_labels', None)
-        xticker_slots= kwargs.get('xticker_slots', None)
-        
-        delta = (ymax - ymin)/4
-        i = 0
-        while True:
-            delta /= 10
-            i += 1
-            if delta < 10:
-                break
-        yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i)))
-        
-        fig, ax = plt.subplots(dpi=450.0)
-        fig.set_size_inches(6.1, 4.2)        
-        line, = ax.plot(data, linewidth=3, color = colour.purple)
-        if baseline is not None:
-            line_baseline, = ax.plot(baseline ,linewidth=3, color = colour.grey)
-
-        if addedline1 is not None:
-            line_addedline1, = ax.plot(addedline1 ,linewidth=3, color = colour.blue)
-        if addedline2 is not None:
-            line_addedline2, = ax.plot(addedline2 ,linewidth=3, color = colour.orange)
-
-            
-        plt.grid()
-        ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
-        
-        ax.set_facecolor('xkcd:white')
-
-        plt.xlabel(xlab, fontsize=9, fontweight = 'bold', horizontalalignment='right', x=0, labelpad=10, 
-                   fontname = font.normal)
-        ax.grid(color='k', linestyle='-', linewidth=0.2)
-        plt.ylabel(ylab, fontsize=9, fontweight = 'bold',
-                   horizontalalignment='right', y=1.0, 
-                   labelpad=10, fontname = font.normal)
-        fig.set_size_inches(6.1, 4.1)
-        plt.xticks(xticker_slots, fontsize=9, fontname = font.normal)
-        plt.yticks(range(ymin, ymax + yinc, yinc), fontsize =9,
-                   fontname = font.normal)
-
-        
-        if (xticker_labels is not None):
-            list_major_labels = xticker_labels
-            list_major_ticks  = xticker_slots
-            ax.xaxis.set_major_locator(ticker.FixedLocator(list_major_ticks))
-            ax.xaxis.set_major_formatter(ticker.FixedFormatter(list_major_labels))
-            #ax.tick_params(axis='x', which='major', colors = colour.light_grey, labelsize=7, rotation=0)
-        
-    
-        # Set text - min & max
-        props = dict(boxstyle='round, pad=0.4',edgecolor=colour.purple,
-                     linewidth = 2, facecolor = 'w', alpha=1)
-        if (min_text is not None):
-            plt.text(min_text[0], min_text[1], int(data.min()), size=min_text[2], rotation=min_text[3], 
-                     ha="center", va="center", color='#660159', bbox=props)        
-        if (max_text is not None):
-            plt.text(max_text[0], max_text[1], int(data.max()), size=max_text[2], rotation=max_text[3], 
-                     ha="center", va="center", color='#660159', bbox=props)
-
-        
-        
-        
-        # Set lengends (if multiple lines)
-        if (baseline is not None):
-            ax.legend([line, line_baseline], list_legends, loc = 'best',
-                      fontsize=9, framealpha=1.0, facecolor = 'w', 
-                      edgecolor='black')
-        if (baseline is not None and addedline1 is not None):
-            ax.legend([line, line_baseline, line_addedline1], list_legends, loc = 'best',
-                      fontsize=9, framealpha=1.0, facecolor = 'w', 
-                      edgecolor='black')
-        if (baseline is not None and addedline1 is not None and addedline2 is not None):
-            ax.legend([line, line_baseline, line_addedline1, line_addedline2], list_legends, loc = 'best',
-                      fontsize=9, framealpha=1.0, facecolor = 'w', 
-                      edgecolor='black')
-
-           
-        ax.set_ylim([ymin, ymax])
-        fig.patch.set_facecolor('w')
-        
-        return fig, ax, props
-    
-    
-    def tow_chart(data, ylab, **kwargs):
-        """Creates a 7 day time of week line chart. Each data point represents 1 hour out of 168 hours.
-
-        Parameters
-        -----------
-        data : array like or scalar
-            Data for the tow chart. Data must only have 168 entries, with row 0 representing Monday at midnight.
-        ylab : str
-            Label for the y axis.
-        ymax : int, optional, default is the max y value
-            The max value of the y axis
-        ymin : int, optional, default is 0
-            The minimum value of the y axis
-        yinc : int, optional
-            The increment of ticks on the y axis.
-
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-        props
-            Dictionary of the text annotation properties
-
-        """
-        import matplotlib.pyplot as plt
-        import matplotlib as mpl
-        import importlib
-        import matplotlib.ticker as ticker
-        import matplotlib.font_manager as font_manager
-        import seaborn as sns
-
-        func()
-        ymax = kwargs.get('ymax', None)
-        ymin = kwargs.get('ymin', 0)
-
-
-        ymax_flag = True
-        if ymax == None:
-            ymax = int(data.max())
-            ymax_flag = False
-
-        delta = (ymax - ymin)/3
-        i = 0
-        while True:
-            delta /= 10
-            i += 1
-            if delta < 10:
-                break
-        yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i)))
-
-        if ymax_flag == True:
-            upper = ymax
-        else:
-            upper = int(3*yinc+ymin)
-
-        fig, ax = plt.subplots(dpi=450.0)
-        ax.plot(data, linewidth = 2.5, color = colour.purple)
-
-        # Commented to view weekday spans 
-        #plt.grid()
-        ax.set_xlim(0, 168)
-        ax.set_facecolor('xkcd:white')
-
-        plt.xlabel('Time of week', fontname = font.normal, fontsize=9, horizontalalignment='left', x=0, labelpad=3, fontweight = 'bold')
-        ax.set_ylim([ymin, upper])
-
-        ax.grid(color='k', linestyle='-', linewidth=0.2)
-        plt.ylabel(ylab, fontname = font.normal, fontsize=9, horizontalalignment='right', y=1, labelpad=7, fontweight = 'bold')
-        fig.set_size_inches(6.1, 1.8)
-
-        ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
-        plt.yticks(range(ymin,upper+int(0.1*yinc), yinc), fontsize =9, fontname = font.normal)
-
-#         # Basic - Y ticks
-#         list_major_ticks  = np.arange(0, 180, 12)
-#         list_major_labels = ['0','12','0','12','0','12','0','12','0','12','0','12','0','12','0']
-
-#         # Experiment-1 - Y ticks (every 3hrs)
-#         list_major_ticks  = np.arange(0, 180, 3)
-#         list_major_labels = ['0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0','3','6','9','12','15','18','21',
-#                              '0']
-
-#         # Experiment-2 - Y ticks (every 6hrs)
-#         list_major_ticks  = np.arange(0, 180, 6)
-#         list_major_labels = ['0','6','12','18',
-#                              '0','6','12','18',
-#                              '0','6','12','18',
-#                              '0','6','12','18',
-#                              '0','6','12','18',
-#                              '0','6','12','18',
-#                              '0','6','12','18',
-#                              '0']
-
-        
-        
-        # Experiment-3 - Y ticks (only 9H & 18H)
-        list_major_ticks  = [0, 9, 18, 24, 33, 42, 48, 57, 66, 72, 81, 90, 96, 105, 114, 120, 129, 138, 144, 153, 162, 168]
-        list_major_labels = ['0','9','18',
-                             '0','9','18',
-                             '0','9','18',
-                             '0','9','18',
-                             '0','9','18',
-                             '0','9','18',
-                             '0','9','18',
-                             '0']               
-        
-        ax.xaxis.set_major_locator(ticker.FixedLocator(list_major_ticks))
-        ax.xaxis.set_major_formatter(ticker.FixedFormatter(list_major_labels))
-        ax.tick_params(axis='x', which='major', colors = colour.light_grey, labelsize=7)
-
-        list_minor_ticks  = list(range(12,180,24))
-        list_minor_labels = ['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday']
-        
-        # Minor ticks location isn't being set correctly with below
-        ax.xaxis.set_minor_locator(ticker.FixedLocator(list_minor_ticks))
-        ax.xaxis.set_minor_formatter(ticker.FixedFormatter(list_minor_labels))
-        ax.tick_params(axis='x',which='minor', colors = 'k', labelsize=9, pad=14)
-
-        props = dict(boxstyle='round, pad=0.3',edgecolor=colour.purple, linewidth = 1.5, facecolor = 'w', alpha=1)
-
-        return fig, ax, props
-
-    def stacked_chart(data_in, xlab, lab1, lab2, **kwargs):
-        """Creates a stacked bar chart comparing 2 sets of data
-        
-        Parameters
-        -----------
-        data : dataframe
-            Data for the stacked bar chart. The dataframe must have 3 columns, the first representing the y ticks, the second representing the baseline, and the third representing the next series of data.
-        xlab : str
-            Label for the x axis.
-        lab1 : str
-            Label in the legend for the baseline
-        lab2 : str
-            Label in the legend fot the next data series
-        xmax : int, optional, default is the max s value
-            The max value of the y axis
-        xmin : int, optional, default is 0
-            The minimum value of the x axis
-        precision : int, optional, default is -1
-            Decimal places in the annotations
-        percent : boolean, optional, default is False
-            Whether the annotations should be formatted as percentages
-            
-        xinc : int, optional
-            The increment of ticks on the x axis.
-        
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-            
-        """
-        
-        func()
-        data = data_in.copy(deep=True)
-        
-        data.columns = ['name', 'values1', 'values2']
-        
-        xmin = kwargs.get('xmin', 0)
-        xmax = kwargs.get('xmax', None)
-        precision = kwargs.get('precision', -1)
-        percent = kwargs.get('percent', False)
-        
-        xmax_flag = True
-        if xmax == None:
-            xmax = int(max(data[['values1', 'values2']].max()))
-            xmax_flag = False
-        
-        delta = (xmax - xmin)/4
-        i = 0
-        while True:
-            delta /= 10
-            i += 1
-            if delta < 10:
-                break
-        xinc = kwargs.get('xinc', int(round(delta+1)*pow(10,i)))
-
-        if xmax_flag == True:
-            upper = xmax
-        else:
-            upper = int(4*xinc+xmin)
-        
-        ind = np.arange(len(data))
-
-        fig, ax = plt.subplots(dpi=450.0)
-        fig.set_size_inches(6.1, len(data))
-        ax.grid(color='k', linestyle='-', linewidth=0.25)
-
-        p1 = ax.barh(ind+0.4, data['values1'], 0.4, align='center', color = colour.grey)
-        p2 = ax.barh(ind, data['values2'], 0.4, align='center', color = colour.purple)
-        ax.xaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
-
-        ax.xaxis.grid(True)
-        ax.yaxis.grid(False)
-        ax.set_yticks(ind+0.4/2)
-        ax.set_xlim(0,upper)
-        ax.set_yticklabels(data['name'])
-        ax.set_xlabel(xlab,  horizontalalignment='left', x=0, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
-
-        ax.set_facecolor('xkcd:white')
-        j=0
-        
-        if precision < 1:
-            data[['values1', 'values2']] = data[['values1', 'values2']].astype(int)
-        for i in data['values2']:
-            if i < 0.1*upper:
-                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
-            else:
-                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
-            j=j+1
-        j=0.4
-        for i in data['values1']:
-            if i < 0.1*upper:
-                ax.annotate(str(format(round(i,precision), ',')), xy=(i+0.015*upper, j-0.05), ha = 'left', color = 'k', fontname = font.normal, fontsize=10)
-            else:
-                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
-            j=j+1
-
-        
-        ax.legend((p1[0], p2[0]), (lab1, lab2), loc=4, frameon=False, prop=font.leg_font)
-        plt.xticks(range(xmin,upper+int(0.1*xinc), xinc), fontname = font.normal, fontsize =10)
-        plt.yticks( fontname = font.normal, fontsize =10)
-        
-        if percent == True:
-            data_yoy = data
-            data_yoy['percent'] = (data['values2']-data['values1'])*100/data['values1']
-            j=0.15
-            for index, row in data_yoy.iterrows():
-                ax.annotate('+'+str(format(int(round(row['percent'],0)), ','))+'%', xy=(max(row[['values1', 'values2']]) + 0.03*upper, j), 
-                                                                                           color = 'k', fontname = font.normal, fontsize=10)
-                j=j+1
-                
-
-        return fig, ax
-    
-    def bar_chart(data_in, xlab, ylab, horizontal=False, **kwargs):
-        """Creates a bar chart
-        
-        Parameters
-        -----------
-        data : dataframe
-            Data for the bar chart. The dataframe must have 2 columns, the first representing the y ticks, and the second representing the data
-        xlab : str
-            Label for the x axis.
-        ylab : str
-            Label for the y axis.
-        horizontal: bool, Alignment of bar_chart
-            True if horizontal else vertical 
-        xymax : int, optional, default is the max s value
-            The max value of the y axis
-        xymin : int, optional, default is 0
-            The minimum value of the x axis
-        precision : int, optional, default is -1
-            Decimal places in the annotations
-            
-        xyinc : int, optional
-            The increment of ticks on the x axis/y axis depending on horizontal bool value.
-        
-        Returns 
-        --------
-        fig
-            Matplotlib fig object
-        ax 
-            Matplotlib ax object
-            
-        """
-        func()
-        data = data_in.copy(deep=True)
-        
-        data.columns = ['name', 'values1']
-        
-        xymin = kwargs.get('xymin', 0)
-        xymax = kwargs.get('xymax', None)
-        precision = kwargs.get('precision', 0)
-        
-        xymax_flag = True
-        if xymax == None:
-            xymax = data['values1'].max()
-            xymax_flag = False
-
-        delta = (xymax - xymin)/4
-        i = 0
-        while True:
-            if delta < 10:
-                break
-            delta /= 10
-            i += 1
-        xyinc = kwargs.get('xyinc', int(round(delta+1)*pow(10,i)))
-
-        if xymax_flag == True:
-            upper = xymax
-        else:
-            upper = int(4*xyinc+xymin)
-        
-        ind = np.arange(len(data))
-
-        fig, ax = plt.subplots(dpi=450.0)
-        fig.set_size_inches(6.1, 4.2)
-#         fig.set_size_inches(6.1, len(data)*0.7)
-        ax.grid(color='k', linestyle='-', linewidth=0.25)
-        if(horizontal):
-            p2 = ax.barh(ind, data['values1'], 0.75, align='center', color = colour.purple)
-            ax.xaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
-            ax.xaxis.grid(True)
-            ax.yaxis.grid(False)
-            ax.set_yticks(ind)
-            ax.set_xlim(0,upper)
-            ax.set_yticklabels(data['name'])
-            ax.set_xlabel(xlab,  horizontalalignment='left', x=0, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
-            if (ylab is not None):
-                ax.set_ylabel(ylab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
-            plt.xticks(range(xymin,upper+int(0.1*xyinc), xyinc), fontname = font.normal, fontsize =10)
-            plt.yticks( fontname = font.normal, fontsize =10)
-        else:
-            p2 = ax.bar(ind, data['values1'], 1.0, align='center', color = colour.purple)
-            ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
-            ax.yaxis.grid(True)
-            ax.xaxis.grid(False)
-            ax.set_xticks(ind)
-            ax.set_ylim(0, upper)
-            ax.set_xticklabels(data['name'], rotation=0.0)
-            ax.set_ylabel(ylab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
-            if (xlab is not None):
-                ax.set_xlabel(xlab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
-            plt.yticks(range(xymin, upper+int(0.1*xyinc), xyinc), fontname = font.normal, fontsize =10)
-            plt.xticks( fontname = font.normal, fontsize =10)            
-
-            
-        ax.set_facecolor('xkcd:white')
-        j=0
-        
-        if precision < 1:
-            data['values1'] = data['values1'].astype(int)
-
-        j=0
-        if (horizontal == True and (precision != -1)):
-            for i in data['values1']:
-                if i < 0.1*upper:
-                    ax.annotate(str(format(round(i, precision), ',')), xy=(i+0.015*upper, j-0.05), ha = 'left', color = 'k', fontname = font.normal, fontsize=10)
-                else:
-                    ax.annotate(str(format(round(i, precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
-                j=j+1
-        elif (horizontal == False and (precision != -1)):
-            for i in data['values1']:
-                if i < 0.1*upper:
-                    ax.annotate(str(format(round(i, precision), ',')), xy=(j-0.15, i+0.015*upper), ha = 'left', color = 'k', fontname = font.normal, fontsize=10, rotation=90.)
-                else:
-                    ax.annotate(str(format(round(i, precision), ',')), xy=(j+0.15, i-0.06*upper), ha = 'right', color = 'w', fontname = font.normal, fontsize=10, rotation=90.)
-                j=j+1
-
-                
+# -*- coding: utf-8 -*-
+#!/usr/bin/env python
+"""
+Version 0.8.0 
+
+"""
+
+from psycopg2 import connect
+import psycopg2.sql as pg
+import pandas.io.sql as pandasql
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import matplotlib.patches as patches
+import matplotlib.ticker as ticker
+import matplotlib.font_manager as font_manager
+import geopandas as gpd
+import os
+import shapely
+import seaborn as sns
+from shapely.geometry import Point
+import numpy as np
+
+class font:
+    """
+    Class defining the global font variables for all functions.
+    
+    """
+    
+    leg_font = font_manager.FontProperties(family='Libre Franklin',size=9)
+    normal = 'Libre Franklin'
+    semibold = 'Libre Franklin SemiBold'
+    
+    
+class colour:
+    """
+    Class defining the global colour variables for all functions.
+    
+    """
+    purple = '#660159'
+    grey = '#7f7e7e'
+    light_grey = '#777777'
+    blue = '#253494'
+    orange = '#0D9F73'
+    cmap = 'YlOrRd'
+    
+class geo:
+    """
+    Class for additional gis layers needed for the cloropleth map.
+    
+    """
+
+    def ttc(con):
+        """Function to return the TTC subway layer.
+        
+        Parameters
+        ------------
+        con : SQL connection object
+            Connection object needed to connect to the RDS
+        
+        Returns
+        --------
+        gdf
+            Geopandas Dataframe of the Subway Layer
+        
+        """
+        query = '''SELECT * FROM gis.subway_to'''
+        
+        ttc = gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom')
+        ttc = ttc.to_crs('epsg:3857')
+        
+        for index, row in ttc.iterrows():
+            rotated = shapely.affinity.rotate(row['geom'], angle=-17, origin = Point(0, 0))
+            ttc.loc[index, 'geom'] = rotated  
+        
+        return ttc 
+    
+    def island(con):
+        
+        """Function to return a layer of the Toronto island. Since the island is classified in the same neighbourhood as the waterfront, in some cases its not completely accurate to show the island shares the same data as the waterfront. 
+        
+        Parameters
+        ------------
+        con : SQL connection object
+            Connection object needed to connect to the RDS
+        
+        Returns
+        --------
+        gdf
+            Geopandas Dataframe of the Toronto island.
+        
+        """
+        
+        query = '''
+
+        SELECT 
+        geom
+        FROM gis.zones_tts06
+        WHERE gta06 = 81
+
+        '''
+
+        island =  gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom')
+        island  = island.to_crs('epsg:3857')
+
+        for index, row in island.iterrows():
+            rotated = shapely.affinity.rotate(row['geom'], angle=-17, origin = Point(0, 0)) 
+            island.loc[index, 'geom'] = rotated
+
+        return island
+     
+    
+class charts:
+    """
+    Class defining all the charting functions.
+    
+    """
+    
+    global func
+    def func():
+        
+        """Function to set global settings for the charts class. 
+        
+        """
+        
+        sns.set(font_scale=1.5) 
+        mpl.rc('font',family='Libre Franklin')
+    
+    def chloro_map(con, df, subway, island, lower, upper, title, **kwargs):
+        """Creates a chloropleth map
+
+        Parameters
+        -----------
+        con : SQL connection object
+                Connection object needed to connect to the RDS
+        df : GeoPandas Dataframe
+                Data for the chloropleth map. The data must only contain 2 columns; the first column has to be the geom column and the second has to be the data that needs to be mapped.
+        lower : int
+                Lower bound for colourmap
+        upper : int
+                Upper bound for the colourmap
+        title : str
+                Legend label
+        cmap : str, optional, default: YlOrRd
+                Matplotlib colourmap to use for the map
+        unit : str, optional
+                Unit to append to the end of the legend tick
+        nbins : int, optional, defualt: 2
+                Number of ticks in the colourmap
+
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+
+        """ 
+
+        cmap = kwargs.get('cmap', colour.cmap)
+        unit = kwargs.get('unit', None)
+        nbins = kwargs.get('nbins', 2)
+
+        df.columns = ['geom', 'values']
+        light = '#d9d9d9'
+
+        fig, ax = plt.subplots(dpi=450.0)
+        fig.set_size_inches(6.69,3.345)
+
+        ax.set_yticklabels([])
+        ax.set_xticklabels([])
+        ax.set_axis_off()
+
+        mpd = df.plot(column='values', ax=ax, vmin=lower, vmax=upper,  cmap = cmap, edgecolor = 'w', linewidth = 0.5)
+
+
+        if subway == True:
+            ttc_df = geo.ttc(con)
+            line = ttc_df.plot( ax=ax, linewidth =4, color = 'w', alpha =0.6) # ttc subway layer
+            line = ttc_df.plot( ax=ax, linewidth =2, color = 'k', alpha =0.4) # ttc subway layer
+
+        if island == False:
+                island_grey = geo.island(con)
+                island_grey.plot(ax=ax, edgecolor = 'w', linewidth = 4,  color = light)
+                island_grey.plot(ax=ax, edgecolor = 'w', linewidth = 0,  color = light)
+
+
+        props = dict(boxstyle='round', facecolor='w', alpha=0)
+        plt.text(0.775, 0.37, title, transform=ax.transAxes, wrap = True, fontsize=7, fontname = font.semibold,
+                verticalalignment='bottom', bbox=props, fontweight = 'bold') # Adding the Legend Title
+
+
+        cax = fig.add_axes([0.718, 0.16, 0.01, 0.22]) # Size of colorbar
+
+        #rect = patches.Rectangle((0.76, 0.01),0.235,0.43,linewidth=0.5, transform=ax.transAxes, edgecolor=light,facecolor='none')
+        #ax.add_patch(rect)
+
+        ax.margins(0.1)
+
+        sm = plt.cm.ScalarMappable(cmap=cmap, norm=plt.Normalize(vmin=lower, vmax=upper))
+        sm._A = []
+        cbr = fig.colorbar(sm, cax=cax)
+        cbr.outline.set_linewidth(0)
+        tick_locator = ticker.MaxNLocator(nbins=nbins)
+        cbr.locator = tick_locator
+        cbr.update_ticks()
+        cbr.ax.yaxis.set_tick_params(width=0.5)
+        cbr.ax.tick_params(labelsize=6)  # Formatting for Colorbar Text
+        for l in cbr.ax.yaxis.get_ticklabels():
+                l.set_family(font.normal)
+
+        if unit is not None:
+            if 0 < upper < 10:
+                ax.text(0.829, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left') 
+            elif 10 <= upper < 100:
+                ax.text(0.839, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
+            elif 100 <= upper < 1000:
+                ax.text(0.851, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
+            elif 1000 <= upper < 100000:
+                ax.text(0.862, 0.32, unit, transform=ax.transAxes, wrap = True, fontsize=6, fontname = font.normal, verticalalignment='bottom', ha = 'left')
+            else:
+                 pass
+
+        return fig, ax
+
+    def histogram_chart(data, ylab, xlab, nbin, **kwargs):
+        """Creates a histogram chart with specified nbin (nbin data)
+        
+        Parameters
+        -----------
+        data : array like or scalar
+            Data for the line chart.
+        ylab : str
+            Label for the y axis.
+        xlab : str
+            Label for the x axis.
+        ymax : int, optional, default is the max y value
+            The max value of the y axis
+        ymin : int, optional, default is 0
+            The minimum value of the y axis
+        
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+        props
+            Dictionary of the text annotation properties
+            
+        """
+        
+        func()
+        xmax = kwargs.get('xmax', None)
+        xmin = kwargs.get('xmin', 0)
+        
+        if (xmax is None):
+            xmax = int(max(data))
+        
+        if (nbin is None):
+            nbin = 10
+        
+        plt.style.use('seaborn-whitegrid')
+        fig, ax = plt.subplots(1,1, dpi=450.0)
+        fig.set_size_inches(6.1, 4.2)
+        ax.hist(data, bins=nbin, alpha=1.0, color=colour.purple)
+        ax.set_xlabel(xlab)
+        ax.set_ylabel(ylab)
+        ax.set_xlim(xmin, xmax)
+        ax.legend(loc='upper right')
+        
+        return fig, ax
+    
+        
+    def line_chart(data, ylab, xlab, **kwargs):
+        """Creates a line chart. x axis must be modified manually
+        
+        Parameters
+        -----------
+        data : array like or scalar
+            Data for the line chart.
+        ylab : str
+            Label for the y axis.
+        xlab : str
+            Label for the x axis.
+        xticker_labels : array, optional, with ticker identifications
+            Tickers for the x axis. 
+        ymax : int, optional, default is the max y value
+            The max value of the y axis
+        ymin : int, optional, default is 0
+            The minimum value of the y axis
+        baseline : array like or scalar, optional, default is None
+            Data for another line representing the baseline.
+        addedline1 : array like or scalar, optional, default is None
+            Data for another line representing the addedline1.
+        addedline2 : array like or scalar, optional, default is None
+            Data for another line representing the addedline2.
+        yinc : int, optional
+            The increment of ticks on the y axis.
+        list_legends: list, optional (when baseline is ON)
+            List of legend names to show on plot
+            
+       min_text : array of min-value text information, default is None
+       max_text : array of max-value text information, default is None
+           
+        
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+        props
+            Dictionary of the text annotation properties
+            
+        """
+        
+        func()
+        ymax = kwargs.get('ymax', int(data.max()))
+        ymin = kwargs.get('ymin', 0)
+        baseline = kwargs.get('baseline', None)
+        addedline1 = kwargs.get('addedline1', None)
+        addedline2 = kwargs.get('addedline2', None)
+        list_legends = kwargs.get('list_legends', None)
+        min_text     = kwargs.get('min_text', None)
+        max_text     = kwargs.get('max_text', None)
+        xticker_labels = kwargs.get('xticker_labels', None)
+        xticker_slots= kwargs.get('xticker_slots', None)
+        
+        delta = (ymax - ymin)/4
+        i = 0
+        while True:
+            delta /= 10
+            i += 1
+            if delta < 10:
+                break
+        yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i)))
+        
+        fig, ax = plt.subplots(dpi=450.0)
+        fig.set_size_inches(6.1, 4.2)        
+        line, = ax.plot(data, linewidth=3, color = colour.purple)
+        if baseline is not None:
+            line_baseline, = ax.plot(baseline ,linewidth=3, color = colour.grey)
+
+        if addedline1 is not None:
+            line_addedline1, = ax.plot(addedline1 ,linewidth=3, color = colour.blue)
+        if addedline2 is not None:
+            line_addedline2, = ax.plot(addedline2 ,linewidth=3, color = colour.orange)
+
+            
+        plt.grid()
+        ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
+        
+        ax.set_facecolor('xkcd:white')
+
+        plt.xlabel(xlab, fontsize=9, fontweight = 'bold', horizontalalignment='right', x=0, labelpad=10, 
+                   fontname = font.normal)
+        ax.grid(color='k', linestyle='-', linewidth=0.2)
+        plt.ylabel(ylab, fontsize=9, fontweight = 'bold',
+                   horizontalalignment='right', y=1.0, 
+                   labelpad=10, fontname = font.normal)
+        fig.set_size_inches(6.1, 4.1)
+        plt.xticks(xticker_slots, fontsize=9, fontname = font.normal)
+        plt.yticks(range(ymin, ymax + yinc, yinc), fontsize =9,
+                   fontname = font.normal)
+
+        
+        if (xticker_labels is not None):
+            list_major_labels = xticker_labels
+            list_major_ticks  = xticker_slots
+            ax.xaxis.set_major_locator(ticker.FixedLocator(list_major_ticks))
+            ax.xaxis.set_major_formatter(ticker.FixedFormatter(list_major_labels))
+            #ax.tick_params(axis='x', which='major', colors = colour.light_grey, labelsize=7, rotation=0)
+        
+    
+        # Set text - min & max
+        props = dict(boxstyle='round, pad=0.4',edgecolor=colour.purple,
+                     linewidth = 2, facecolor = 'w', alpha=1)
+        if (min_text is not None):
+            plt.text(min_text[0], min_text[1], int(data.min()), size=min_text[2], rotation=min_text[3], 
+                     ha="center", va="center", color='#660159', bbox=props)        
+        if (max_text is not None):
+            plt.text(max_text[0], max_text[1], int(data.max()), size=max_text[2], rotation=max_text[3], 
+                     ha="center", va="center", color='#660159', bbox=props)
+
+        
+        
+        
+        # Set lengends (if multiple lines)
+        if (baseline is not None):
+            ax.legend([line, line_baseline], list_legends, loc = 'best',
+                      fontsize=9, framealpha=1.0, facecolor = 'w', 
+                      edgecolor='black')
+        if (baseline is not None and addedline1 is not None):
+            ax.legend([line, line_baseline, line_addedline1], list_legends, loc = 'best',
+                      fontsize=9, framealpha=1.0, facecolor = 'w', 
+                      edgecolor='black')
+        if (baseline is not None and addedline1 is not None and addedline2 is not None):
+            ax.legend([line, line_baseline, line_addedline1, line_addedline2], list_legends, loc = 'best',
+                      fontsize=9, framealpha=1.0, facecolor = 'w', 
+                      edgecolor='black')
+
+           
+        ax.set_ylim([ymin, ymax])
+        fig.patch.set_facecolor('w')
+        
+        return fig, ax, props
+    
+    
+    def tow_chart(data, ylab, **kwargs):
+        """Creates a 7 day time of week line chart. Each data point represents 1 hour out of 168 hours.
+
+        Parameters
+        -----------
+        data : array like or scalar
+            Data for the tow chart. Data must only have 168 entries, with row 0 representing Monday at midnight.
+        ylab : str
+            Label for the y axis.
+        ymax : int, optional, default is the max y value
+            The max value of the y axis
+        ymin : int, optional, default is 0
+            The minimum value of the y axis
+        yinc : int, optional
+            The increment of ticks on the y axis.
+
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+        props
+            Dictionary of the text annotation properties
+
+        """
+        import matplotlib.pyplot as plt
+        import matplotlib as mpl
+        import importlib
+        import matplotlib.ticker as ticker
+        import matplotlib.font_manager as font_manager
+        import seaborn as sns
+
+        func()
+        ymax = kwargs.get('ymax', None)
+        ymin = kwargs.get('ymin', 0)
+
+
+        ymax_flag = True
+        if ymax == None:
+            ymax = int(data.max())
+            ymax_flag = False
+
+        delta = (ymax - ymin)/3
+        i = 0
+        while True:
+            delta /= 10
+            i += 1
+            if delta < 10:
+                break
+        yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i)))
+
+        if ymax_flag == True:
+            upper = ymax
+        else:
+            upper = int(3*yinc+ymin)
+
+        fig, ax = plt.subplots(dpi=450.0)
+        ax.plot(data, linewidth = 2.5, color = colour.purple)
+
+        # Commented to view weekday spans 
+        #plt.grid()
+        ax.set_xlim(0, 168)
+        ax.set_facecolor('xkcd:white')
+
+        plt.xlabel('Time of week', fontname = font.normal, fontsize=9, horizontalalignment='left', x=0, labelpad=3, fontweight = 'bold')
+        ax.set_ylim([ymin, upper])
+
+        ax.grid(color='k', linestyle='-', linewidth=0.2)
+        plt.ylabel(ylab, fontname = font.normal, fontsize=9, horizontalalignment='right', y=1, labelpad=7, fontweight = 'bold')
+        fig.set_size_inches(6.1, 1.8)
+
+        ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
+        plt.yticks(range(ymin,upper+int(0.1*yinc), yinc), fontsize =9, fontname = font.normal)
+
+#         # Basic - Y ticks
+#         list_major_ticks  = np.arange(0, 180, 12)
+#         list_major_labels = ['0','12','0','12','0','12','0','12','0','12','0','12','0','12','0']
+
+#         # Experiment-1 - Y ticks (every 3hrs)
+#         list_major_ticks  = np.arange(0, 180, 3)
+#         list_major_labels = ['0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0','3','6','9','12','15','18','21',
+#                              '0']
+
+#         # Experiment-2 - Y ticks (every 6hrs)
+#         list_major_ticks  = np.arange(0, 180, 6)
+#         list_major_labels = ['0','6','12','18',
+#                              '0','6','12','18',
+#                              '0','6','12','18',
+#                              '0','6','12','18',
+#                              '0','6','12','18',
+#                              '0','6','12','18',
+#                              '0','6','12','18',
+#                              '0']
+
+        
+        
+        # Experiment-3 - Y ticks (only 9H & 18H)
+        list_major_ticks  = [0, 9, 18, 24, 33, 42, 48, 57, 66, 72, 81, 90, 96, 105, 114, 120, 129, 138, 144, 153, 162, 168]
+        list_major_labels = ['0','9','18',
+                             '0','9','18',
+                             '0','9','18',
+                             '0','9','18',
+                             '0','9','18',
+                             '0','9','18',
+                             '0','9','18',
+                             '0']               
+        
+        ax.xaxis.set_major_locator(ticker.FixedLocator(list_major_ticks))
+        ax.xaxis.set_major_formatter(ticker.FixedFormatter(list_major_labels))
+        ax.tick_params(axis='x', which='major', colors = colour.light_grey, labelsize=7)
+
+        list_minor_ticks  = list(range(12,180,24))
+        list_minor_labels = ['Monday','Tuesday','Wednesday','Thursday','Friday','Saturday','Sunday']
+        
+        # Minor ticks location isn't being set correctly with below
+        ax.xaxis.set_minor_locator(ticker.FixedLocator(list_minor_ticks))
+        ax.xaxis.set_minor_formatter(ticker.FixedFormatter(list_minor_labels))
+        ax.tick_params(axis='x',which='minor', colors = 'k', labelsize=9, pad=14)
+
+        props = dict(boxstyle='round, pad=0.3',edgecolor=colour.purple, linewidth = 1.5, facecolor = 'w', alpha=1)
+
+        return fig, ax, props
+
+    def stacked_chart(data_in, xlab, lab1, lab2, **kwargs):
+        """Creates a stacked bar chart comparing 2 sets of data
+        
+        Parameters
+        -----------
+        data : dataframe
+            Data for the stacked bar chart. The dataframe must have 3 columns, the first representing the y ticks, the second representing the baseline, and the third representing the next series of data.
+        xlab : str
+            Label for the x axis.
+        lab1 : str
+            Label in the legend for the baseline
+        lab2 : str
+            Label in the legend fot the next data series
+        xmax : int, optional, default is the max s value
+            The max value of the y axis
+        xmin : int, optional, default is 0
+            The minimum value of the x axis
+        precision : int, optional, default is -1
+            Decimal places in the annotations
+        percent : boolean, optional, default is False
+            Whether the annotations should be formatted as percentages
+            
+        xinc : int, optional
+            The increment of ticks on the x axis.
+        
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+            
+        """
+        
+        func()
+        data = data_in.copy(deep=True)
+        
+        data.columns = ['name', 'values1', 'values2']
+        
+        xmin = kwargs.get('xmin', 0)
+        xmax = kwargs.get('xmax', None)
+        precision = kwargs.get('precision', -1)
+        percent = kwargs.get('percent', False)
+        
+        xmax_flag = True
+        if xmax == None:
+            xmax = int(max(data[['values1', 'values2']].max()))
+            xmax_flag = False
+        
+        delta = (xmax - xmin)/4
+        i = 0
+        while True:
+            delta /= 10
+            i += 1
+            if delta < 10:
+                break
+        xinc = kwargs.get('xinc', int(round(delta+1)*pow(10,i)))
+
+        if xmax_flag == True:
+            upper = xmax
+        else:
+            upper = int(4*xinc+xmin)
+        
+        ind = np.arange(len(data))
+
+        fig, ax = plt.subplots(dpi=450.0)
+        fig.set_size_inches(6.1, len(data))
+        ax.grid(color='k', linestyle='-', linewidth=0.25)
+
+        p1 = ax.barh(ind+0.4, data['values1'], 0.4, align='center', color = colour.grey)
+        p2 = ax.barh(ind, data['values2'], 0.4, align='center', color = colour.purple)
+        ax.xaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
+
+        ax.xaxis.grid(True)
+        ax.yaxis.grid(False)
+        ax.set_yticks(ind+0.4/2)
+        ax.set_xlim(0,upper)
+        ax.set_yticklabels(data['name'])
+        ax.set_xlabel(xlab,  horizontalalignment='left', x=0, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
+
+        ax.set_facecolor('xkcd:white')
+        j=0
+        
+        if precision < 1:
+            data[['values1', 'values2']] = data[['values1', 'values2']].astype(int)
+        for i in data['values2']:
+            if i < 0.1*upper:
+                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
+            else:
+                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
+            j=j+1
+        j=0.4
+        for i in data['values1']:
+            if i < 0.1*upper:
+                ax.annotate(str(format(round(i,precision), ',')), xy=(i+0.015*upper, j-0.05), ha = 'left', color = 'k', fontname = font.normal, fontsize=10)
+            else:
+                ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
+            j=j+1
+
+        
+        ax.legend((p1[0], p2[0]), (lab1, lab2), loc=4, frameon=False, prop=font.leg_font)
+        plt.xticks(range(xmin,upper+int(0.1*xinc), xinc), fontname = font.normal, fontsize =10)
+        plt.yticks( fontname = font.normal, fontsize =10)
+        
+        if percent == True:
+            data_yoy = data
+            data_yoy['percent'] = (data['values2']-data['values1'])*100/data['values1']
+            j=0.15
+            for index, row in data_yoy.iterrows():
+                ax.annotate('+'+str(format(int(round(row['percent'],0)), ','))+'%', xy=(max(row[['values1', 'values2']]) + 0.03*upper, j), 
+                                                                                           color = 'k', fontname = font.normal, fontsize=10)
+                j=j+1
+                
+
+        return fig, ax
+    
+    def bar_chart(data_in, xlab, ylab, horizontal=False, **kwargs):
+        """Creates a bar chart
+        
+        Parameters
+        -----------
+        data : dataframe
+            Data for the bar chart. The dataframe must have 2 columns, the first representing the y ticks, and the second representing the data
+        xlab : str
+            Label for the x axis.
+        ylab : str
+            Label for the y axis.
+        horizontal: bool, Alignment of bar_chart
+            True if horizontal else vertical 
+        xymax : int, optional, default is the max s value
+            The max value of the y axis
+        xymin : int, optional, default is 0
+            The minimum value of the x axis
+        precision : int, optional, default is -1
+            Decimal places in the annotations
+            
+        xyinc : int, optional
+            The increment of ticks on the x axis/y axis depending on horizontal bool value.
+        
+        Returns 
+        --------
+        fig
+            Matplotlib fig object
+        ax 
+            Matplotlib ax object
+            
+        """
+        func()
+        data = data_in.copy(deep=True)
+        
+        data.columns = ['name', 'values1']
+        
+        xymin = kwargs.get('xymin', 0)
+        xymax = kwargs.get('xymax', None)
+        precision = kwargs.get('precision', 0)
+        
+        xymax_flag = True
+        if xymax == None:
+            xymax = data['values1'].max()
+            xymax_flag = False
+
+        delta = (xymax - xymin)/4
+        i = 0
+        while True:
+            if delta < 10:
+                break
+            delta /= 10
+            i += 1
+        xyinc = kwargs.get('xyinc', int(round(delta+1)*pow(10,i)))
+
+        if xymax_flag == True:
+            upper = xymax
+        else:
+            upper = int(4*xyinc+xymin)
+        
+        ind = np.arange(len(data))
+
+        fig, ax = plt.subplots(dpi=450.0)
+        fig.set_size_inches(6.1, 4.2)
+#         fig.set_size_inches(6.1, len(data)*0.7)
+        ax.grid(color='k', linestyle='-', linewidth=0.25)
+        if(horizontal):
+            p2 = ax.barh(ind, data['values1'], 0.75, align='center', color = colour.purple)
+            ax.xaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
+            ax.xaxis.grid(True)
+            ax.yaxis.grid(False)
+            ax.set_yticks(ind)
+            ax.set_xlim(0,upper)
+            ax.set_yticklabels(data['name'])
+            ax.set_xlabel(xlab,  horizontalalignment='left', x=0, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
+            if (ylab is not None):
+                ax.set_ylabel(ylab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
+            plt.xticks(range(xymin,upper+int(0.1*xyinc), xyinc), fontname = font.normal, fontsize =10)
+            plt.yticks( fontname = font.normal, fontsize =10)
+        else:
+            p2 = ax.bar(ind, data['values1'], 1.0, align='center', color = colour.purple)
+            ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}'))
+            ax.yaxis.grid(True)
+            ax.xaxis.grid(False)
+            ax.set_xticks(ind)
+            ax.set_ylim(0, upper)
+            ax.set_xticklabels(data['name'], rotation=0.0)
+            ax.set_ylabel(ylab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
+            if (xlab is not None):
+                ax.set_xlabel(xlab, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold')
+            plt.yticks(range(xymin, upper+int(0.1*xyinc), xyinc), fontname = font.normal, fontsize =10)
+            plt.xticks( fontname = font.normal, fontsize =10)            
+
+            
+        ax.set_facecolor('xkcd:white')
+        j=0
+        
+        if precision < 1:
+            data['values1'] = data['values1'].astype(int)
+
+        j=0
+        if (horizontal == True and (precision != -1)):
+            for i in data['values1']:
+                if i < 0.1*upper:
+                    ax.annotate(str(format(round(i, precision), ',')), xy=(i+0.015*upper, j-0.05), ha = 'left', color = 'k', fontname = font.normal, fontsize=10)
+                else:
+                    ax.annotate(str(format(round(i, precision), ',')), xy=(i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10)
+                j=j+1
+        elif (horizontal == False and (precision != -1)):
+            for i in data['values1']:
+                if i < 0.1*upper:
+                    ax.annotate(str(format(round(i, precision), ',')), xy=(j-0.15, i+0.015*upper), ha = 'left', color = 'k', fontname = font.normal, fontsize=10, rotation=90.)
+                else:
+                    ax.annotate(str(format(round(i, precision), ',')), xy=(j+0.15, i-0.06*upper), ha = 'right', color = 'w', fontname = font.normal, fontsize=10, rotation=90.)
+                j=j+1
+
+                
         return fig, ax
\ No newline at end of file