From f88240b71d93d60b8a1c3d53009ddde8d08acc64 Mon Sep 17 00:00:00 2001 From: Zhangyixue1537 Date: Thu, 21 Dec 2023 19:43:41 +0000 Subject: [PATCH] #8 add 11th rick.py to rick_try --- rick.py | 599 +++++++++++++++++++++++--------------------------------- 1 file changed, 244 insertions(+), 355 deletions(-) diff --git a/rick.py b/rick.py index 0c1f4d9..f250cfc 100644 --- a/rick.py +++ b/rick.py @@ -1,8 +1,6 @@ # -*- coding: utf-8 -*- """ Version 0.8.0 - - """ from psycopg2 import connect import psycopg2.sql as pg @@ -24,17 +22,18 @@ class font: Class defining the global font variables for all functions. """ - + leg_font = font_manager.FontProperties(family='DejaVu Sans',size=9) normal = 'DejaVu Sans' semibold = 'DejaVu Sans SemiBold' - - -class colour: + + +class colour(): """ Class defining the global colour variables for all functions. """ + purple = '#660159' grey = '#7f7e7e' orange = '#d95f02' @@ -42,15 +41,29 @@ class colour: blue = '#253494' light_grey = '#777777' cmap = 'YlOrRd' - teal = '#23a87f' - blue_grey = '#1b5872' + + # Purple shades + purple_0 = '#440436' + purple_1 = '#550347' + purple_2 = '#660159' + purple_3 = '#9c7b94' + purple_4 = '#c0abbb' + colours_map = { + 1: purple_1, + 2: purple_2, + 3: purple_3, + 4: light_grey + } + def get_colour_from_index(self, index): + return self.colours_map[index] + class geo: """ Class for additional gis layers needed for the cloropleth map. """ - + def ttc(con): """Function to return the TTC subway layer. @@ -73,18 +86,18 @@ def ttc(con): ttc = gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom') # ttc = ttc.to_crs({'init' :'epsg:3857'}) ttc = ttc.to_crs(epsg=3857) - + # Below can be replaced by an apply lambda # in case one row is of a different type (e.g. MULTIPOLYGON vs POLYGON) #for index, row in ttc.iterrows(): # rotated = shapely.affinity.rotate(row['geom'], angle=-17, origin = Point(0, 0)) # ttc.loc[index, 'geom'] = rotated ttc['geom']=ttc['geom'].apply(lambda x: shapely.affinity.rotate(x, angle=-17, origin = Point(0, 0))) - + 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 @@ -98,14 +111,12 @@ def island(con): Geopandas Dataframe of the Toronto island. """ - - query = ''' + query = ''' SELECT geom FROM tts.zones_tts06 WHERE gta06 = 81 - ''' island = gpd.GeoDataFrame.from_postgis(query, con, geom_col='geom') @@ -120,23 +131,23 @@ def island(con): island['geom']=island['geom'].apply(lambda x: shapely.affinity.rotate(x, angle=-17, origin = Point(0, 0))) 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='DejaVu Sans') - + def chloro_map(con, df, lower, upper, title, **kwargs): """Creates a chloropleth map @@ -171,49 +182,49 @@ def chloro_map(con, df, lower, upper, title, **kwargs): Matplotlib ax object """ - + func() subway = kwargs.get('subway', False) island = kwargs.get('island', True) 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() 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 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) - + 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 - - + + 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) @@ -225,7 +236,7 @@ def chloro_map(con, df, lower, upper, title, **kwargs): 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') @@ -237,10 +248,10 @@ def chloro_map(con, df, lower, upper, title, **kwargs): 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 line_chart(data, ylab, xlab, **kwargs): """Creates a line chart. x axis must be modified manually @@ -271,12 +282,12 @@ def line_chart(data, ylab, xlab, **kwargs): Dictionary of the text annotation properties """ - + func() ymax = kwargs.get('ymax', int(data.max())) ymin = kwargs.get('ymin', 0) baseline = kwargs.get('baseline', None) - + delta = (ymax - ymin)/4 i = 0 while True: @@ -285,7 +296,7 @@ def line_chart(data, ylab, xlab, **kwargs): if delta < 10: break yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i))) - + fig, ax =plt.subplots() ax.plot(data ,linewidth=3, color = colour.purple) if baseline is not None: @@ -312,9 +323,9 @@ def line_chart(data, ylab, xlab, **kwargs): 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. @@ -344,13 +355,13 @@ def tow_chart(data, ylab, **kwargs): 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: @@ -359,12 +370,12 @@ def tow_chart(data, ylab, **kwargs): 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() ax.plot(data, linewidth = 2.5, color = colour.purple) @@ -431,22 +442,22 @@ def stacked_chart(data_in, xlab, lab1, lab2, **kwargs): 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: @@ -460,7 +471,7 @@ def stacked_chart(data_in, xlab, lab1, lab2, **kwargs): upper = xmax else: upper = int(4*xinc+xmin) - + ind = np.arange(len(data)) fig, ax = plt.subplots() @@ -480,7 +491,7 @@ def stacked_chart(data_in, xlab, lab1, lab2, **kwargs): ax.set_facecolor('xkcd:white') j=0 - + if precision < 1: data[['values1', 'values2']] = data[['values1', 'values2']].astype(int) for i in data['values2']: @@ -492,16 +503,16 @@ def stacked_chart(data_in, xlab, lab1, lab2, **kwargs): 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-0.07), ha = 'left', color = 'k', fontname = font.normal, fontsize=10) + 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-0.07), ha = 'right', color = 'w', fontname = font.normal, fontsize=10) + 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'] @@ -510,138 +521,10 @@ def stacked_chart(data_in, xlab, lab1, lab2, **kwargs): ax.annotate(('+' if row['percent'] > 0 else '')+str(format(int(round(row['percent'],0)), ','))+'%', xy=(max(row[['values1', 'values2']]) + (0.12 if row['values2'] < 0.1*upper else 0.03)*upper, j), color = 'k', fontname = font.normal, fontsize=10) j=j+1 - - return fig, ax - def multi_stacked_bar_chart(data_in, xlab, lab1, lab2, lab3, **kwargs): - """Creates a stacked bar chart with 3 bar stacks - - 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 - lab3 : 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 - [DSIABLED] 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', 'values3'] - - 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', 'values3']].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() - fig.set_size_inches(6.1, len(data)) - ax.grid(color='k', linestyle='-', linewidth=0.25) - p1 = ax.barh(ind, data['values1'], 0.4, align='center', color = colour.grey) - p2 = ax.barh(ind, data['values2'], 0.4, align='center', color = colour.purple, left = data['values1']) - p3 = ax.barh(ind, data['values3'], 0.4, align='center', color = colour.teal, left = (data['values1'] + data['values2'])) - 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') - ax.set_facecolor('xkcd:white') - - # if precision < 1: # removed this so it does not round or cast to int prematurely. Also, casting to int truncates the decimal WITHOUT rounding. - # data[['values1', 'values2','values3']] = data[['values1', 'values2','values3']].astype(int) - horiz_nudge = 0.2 - for index, i in enumerate(data['values3']): - offset = data['values3'][index]+ data['values2'][index] + data['values1'][index] - # if value is less than 0.5%, do not show data label, if less than 4%, show data label above the bar, else show label on the bar - if i < 0.5: - continue - if i < 4: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index+0.3), ha = 'center', color = 'k', fontname = font.normal, fontsize=10) - else: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index-0.07), ha = 'center', color = 'w', fontname = font.normal, fontsize=10) - for index, i in enumerate(data['values2']): - offset = data['values2'][index] + data['values1'][index] - if i < 0.5: - continue - if i < 4: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index+0.3), ha = 'center', color = 'k', fontname = font.normal, fontsize=10) - else: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index-0.07), ha = 'center', color = 'w', fontname = font.normal, fontsize=10) - for index, i in enumerate(data['values1']): - offset = data['values1'][index] - if i < 0.5: - continue - if i < 4: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index+0.3), ha = 'center', color = 'k', fontname = font.normal, fontsize=10) - else: - ax.annotate(str(format(round(i,precision), ',')), xy=((offset+offset-i)/2+horiz_nudge, index-0.07), ha = 'center', color = 'w', fontname = font.normal, fontsize=10) - - # ax.legend((p1[0], p2[0], p3[0]), (lab1, lab2, lab3), bbox_to_anchor=(1.05, 1.0), loc='upper left', frameon=False, prop=font.leg_font) - ax.legend((p1[0], p2[0], p3[0]), (lab1, lab2, lab3), bbox_to_anchor=(0.5, 1.15), loc='upper center', ncol=3, frameon=False, prop=font.leg_font) - plt.subplots_adjust(bottom=0.2) # Adjust layout to make room for the legend above the plot - 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(('+' if row['percent'] > 0 else '')+str(format(int(round(row['percent'],0)), ','))+'%', - # xy=(max(row[['values1', 'values2']]) + (0.12 if row['values2'] < 0.1*upper else 0.03)*upper, j), color = 'k', fontname = font.normal, fontsize=10) - # j=j+1 return fig, ax - + def stacked_chart_quad(data_in, xlab, lab1, lab2, lab3, lab4, **kwargs): """Creates a stacked bar chart comparing 4 sets of data @@ -675,22 +558,22 @@ def stacked_chart_quad(data_in, xlab, lab1, lab2, lab3, lab4, **kwargs): Matplotlib ax object """ - + func() data = data_in.copy(deep=True) - + data.columns = ['name', 'values1', 'values2', 'values3', 'values4'] - + 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', 'values3', 'values4']].max())) xmax_flag = False - + delta = (xmax - xmin)/4 i = 0 while True: @@ -704,9 +587,8 @@ def stacked_chart_quad(data_in, xlab, lab1, lab2, lab3, lab4, **kwargs): upper = xmax else: upper = int(4*xinc+xmin) - + ind = np.arange(len(data)) - print(len(data)) fig, ax = plt.subplots() fig.set_size_inches(6.1, len(data)*1.5) @@ -726,11 +608,11 @@ def stacked_chart_quad(data_in, xlab, lab1, lab2, lab3, lab4, **kwargs): ax.set_xlabel(xlab, horizontalalignment='left', x=0, labelpad=10, fontname = font.normal, fontsize=10, fontweight = 'bold') ax.set_facecolor('xkcd:white') - - + + if precision < 1: data[['values1', 'values2', 'values3', 'values4']] = data[['values1', 'values2', 'values3', 'values4']].astype(int) - + j = 0.0 for k in range(4,0,-1): @@ -741,29 +623,27 @@ def stacked_chart_quad(data_in, xlab, lab1, lab2, lab3, lab4, **kwargs): 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 = j-len(data[f'values{k}']) + 0.2 - + ax.legend((p1[0], p2[0], p3[0], p4[0]), (lab1, lab2, lab3, lab4), 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: j = 0.15 data_yoy = data for k in range(3,0,-1): data_yoy[f'percent{k}'] = (data['values4']-data[f'values{k}'])*100/data[f'values{k}'] - if k == 1: - print(data_yoy) - + for index, row in data_yoy.iterrows(): ax.annotate(('+' if row[f'percent{k}'] > 0 else '')+str(format(int(round(row[f'percent{k}'],0)), ','))+'%', xy=(max(row[['values1', 'values2', 'values3', 'values4']]) + (0.12 if row['values4'] < 0.1*upper else 0.03)*upper, j), color = 'k', fontname = font.normal, fontsize=10) j+=1 j = j-len(data_yoy) + 0.2 - + return fig, ax - + def bar_chart(data_in, xlab,**kwargs): """Creates a bar chart @@ -793,13 +673,13 @@ def bar_chart(data_in, xlab,**kwargs): """ func() data = data_in.copy(deep=True) - + data.columns = ['name', 'values1'] - + xmin = kwargs.get('xmin', 0) xmax = kwargs.get('xmax', None) precision = kwargs.get('precision', 0) - + xmax_flag = True if xmax == None: xmax = data['values1'].max() @@ -818,7 +698,7 @@ def bar_chart(data_in, xlab,**kwargs): upper = xmax else: upper = int(4*xinc+xmin) - + ind = np.arange(len(data)) fig, ax = plt.subplots() @@ -836,7 +716,7 @@ def bar_chart(data_in, xlab,**kwargs): ax.set_facecolor('xkcd:white') j=0 - + if precision < 1: data['values1'] = data['values1'].astype(int) @@ -848,124 +728,10 @@ def bar_chart(data_in, xlab,**kwargs): 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 - - plt.xticks(range(xmin,upper+int(0.1*xinc), xinc), fontname = font.normal, fontsize =10) - plt.yticks( fontname = font.normal, fontsize =10) - - return fig, ax - - - def bar_chart_stacked_on_top(data_in, xlab, lab1, lab2, **kwargs): - """Creates a stacked (not grouped) bar chart with 2 sets of data. Bars are plotted such that the max value of the 1st bar is the start of the 2nd bar - - 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(sum(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() - fig.set_size_inches(6.1, len(data)*0.7) - ax.grid(color='k', linestyle='-', linewidth=0.25) - - p1 = ax.barh(ind, data['values1'], height = 0.75, align='center', color = colour.purple) - p2 = ax.barh(ind, data['values2'], left = list(data['values1']), height = 0.75, align='center', color = colour.grey) - 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') - - ax.set_facecolor('xkcd:white') - j=0 - - if precision < 1: - data[['values1', 'values2']] = data[['values1', 'values2']].astype(int) - # annotate data labels for each stacked bar - for idx, i in enumerate(data['values2']): - if i < 0.1*upper: - ax.annotate(str(format(round(i,precision), ',')), xy=(data['values1'][idx]+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=(data['values1'][idx]+i-0.015*upper, j-0.05), ha = 'right', color = 'w', fontname = font.normal, fontsize=10) - j=j+1 - j = 0 - for i in data['values1']: - if i < 0.1*upper: - ax.annotate(str(format(round(i,precision), ',')), xy=(i+0.015*upper, j-0.07), ha = 'left', color = 'k', fontname = font.normal, fontsize=10) - else: - ax.annotate(str(format(round(i,precision), ',')), xy=(i-0.015*upper, j-0.07), ha = 'right', color = 'w', fontname = font.normal, fontsize=10) - j=j+1 - ax.legend((p1[0], p2[0]), (lab1, lab2), loc='best', 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(('+' if row['percent'] > 0 else '')+str(format(int(round(row['percent'],0)), ','))+'%', - xy=(max(row[['values1', 'values2']]) + (0.12 if row['values2'] < 0.1*upper else 0.03)*upper, j), color = 'k', fontname = font.normal, fontsize=10) - j=j+1 - + return fig, ax @@ -977,13 +743,13 @@ def multi_linechart(df_line, sett): ''' df=df_line.copy() - + # ---------------------------------------------- # Setup the figure fig, ax =plt.subplots(1) fig.set_size_inches(18, 5) ax = plt.gca() - + # ---------------------------------------------- # Default styling params if not defined in sett if 'body' in sett: @@ -1008,11 +774,11 @@ def multi_linechart(df_line, sett): 'fontfamily-list':['Libre Franklin', 'DejaVu Sans'], 'stroke':'#000000', 'stroke-width':2, 'border':'solid' } - + mpl.rcParams['font.family'] = dflt['font-family'] if dflt['font-family']=='sans-serif': mpl.rcParams['font.sans-serif']=dflt['fontfamily-list'] - + # mpl.rcParams.update({ # 'font.size': dflt['font-size'], # 'font.family': dflt['font-family'] @@ -1023,19 +789,19 @@ def multi_linechart(df_line, sett): # actually gets set. So just before calling the function, # make sure you set it again... # ---------------------------------------------------------------- - + # ---------------------------------------------- # Define line-number-dependent params num_lines=df.shape[1] - 1 - + col_names=['xcol'] ymax_array=[] for n in range(num_lines): col_names.append('ycol_' + str(n)) ymax_array.append(df.iloc[:,n+1].max()) - + df.columns=col_names - + # ---------------------------------------------- # title if 'title' in sett: @@ -1047,7 +813,7 @@ def multi_linechart(df_line, sett): loc=('center' if 'loc' not in sett['title_params'] else sett['title_params']['loc']) ax.set_title(sett['title'], fontsize=title_size, loc=loc) - + # ---------------------------------------------- # grid if 'major_grid_on' in sett and sett['major_grid_on']==True: @@ -1070,14 +836,14 @@ def multi_linechart(df_line, sett): c='gray' b='-' plt.grid(b=True, which='minor', color=c, linestyle=b) - + # ---------------------------------------------- # axes (both) mpl.rcParams['axes.linewidth'] = 0.3 ticklength=2 if 'ticklength' not in sett else sett['ticklength'] tickwidth=1 if 'tickwidth' not in sett else sett['tickwidth'] ax.tick_params(width=tickwidth, length=ticklength) - + # y-axis if 'yaxis' in sett: ymin=(0 if 'ymin' not in sett['yaxis'] @@ -1085,7 +851,7 @@ def multi_linechart(df_line, sett): ymax=(np.max(ymax_array)*(1 + 0.1) if 'ymax' not in sett['yaxis'] else sett['yaxis']['ymax']) - + # y-axis label label=('' if 'label' not in sett['yaxis'] else sett['yaxis']['label']) @@ -1093,13 +859,13 @@ def multi_linechart(df_line, sett): not in sett['yaxis'] else sett['yaxis']['labelsize']) plt.ylabel(label, fontsize=labelsize) - + # Format y-axis tick labels ticklabelsize=(dflt['font-size'] if 'ticklabelsize' not in sett['yaxis'] else sett['yaxis']['ticklabelsize']) ax.tick_params(axis='y', labelsize=ticklabelsize) - + # comma format precision=('.0f' if 'precision' not in sett['yaxis'] @@ -1110,7 +876,7 @@ def multi_linechart(df_line, sett): else: ymin=0 ymax=np.max(ymax_array)*(1 + 0.1) - + delta = (ymax - ymin)/4 i = 0 while True: @@ -1122,9 +888,9 @@ def multi_linechart(df_line, sett): yinc=sett['yinc'] else: yinc = int(round(delta+1)*pow(10,i)) - + plt.ylim(top=ymax, bottom=ymin) - + # ---------------------------------------------- # x-axis if 'xaxis' in sett: @@ -1135,7 +901,7 @@ def multi_linechart(df_line, sett): not in sett['xaxis'] else sett['xaxis']['labelsize']) plt.xlabel(label, fontsize=labelsize) - + # x-axis tick labels if 'major_loc' in sett['xaxis']: # x-values are dates date_form_mjr = sett['xaxis']['major_loc']['date_form'] @@ -1143,7 +909,7 @@ def multi_linechart(df_line, sett): if 'minor_loc' in sett['xaxis']: date_form_mnr = sett['xaxis']['minor_loc']['date_form'] ax.xaxis.set_minor_locator(date_form_mnr) - + # x-axis tick label size ticklabelsize=(dflt['font-size'] if 'ticklabelsize' not in sett['xaxis'] @@ -1154,7 +920,7 @@ def multi_linechart(df_line, sett): # Default x-axis tick lines ax.tick_params(axis='x', labelsize=dflt['font-size'], labelbottom=True) - + # ---------------------------------------------- # Plot data and legend if 'legend' in sett: @@ -1162,7 +928,7 @@ def multi_linechart(df_line, sett): else sett['legend']['loc']) leg_array=[] custom_lines=[] - + for n in range(num_lines): if 'lines' in sett: line_colour=(dflt['stroke'] if 'stroke' not in @@ -1178,10 +944,10 @@ def multi_linechart(df_line, sett): line_colour=dflt['stroke'] line_width=dflt['stroke-width'] border_style=dflt['border'] - + ax.plot(df['xcol'], df['ycol_' + str(n)], linewidth=line_width, color = line_colour, linestyle=border_style) - + # Legend if 'legend' in sett: leg_array.append(sett['lines'][n]['label']) @@ -1190,17 +956,17 @@ def multi_linechart(df_line, sett): lw=line_width, linestyle=border_style) ) - + if 'legend' in sett: ax.legend(custom_lines, leg_array, loc=legend_loc, prop={"size": dflt['font-size']}, ncol=len(df.columns)) - + # ---------------------------------------------- # Plot shaded areas if 'shaded' in sett: num_a=len(sett['shaded'].keys()) - + for area in range(num_a): idx=sett['shaded'][area]['lims'] facecolour=sett['shaded'][area]['fill'] @@ -1208,16 +974,16 @@ def multi_linechart(df_line, sett): else sett['shaded'][area]['zorder']) alpha=(1 if 'alpha' not in sett['shaded'][area] else sett['shaded'][area]['alpha']) - + # Shaded area left and right bds for i in range(len(idx)): bd1=idx[i][0] bd2=idx[i][1] - + ax.axvspan(bd1, bd2, facecolor=facecolour, edgecolor='none', alpha=alpha, zorder=zorder) - + # Shaded area label if 'label' in sett['shaded'][area]: rot=(0 if 'rotation' not in @@ -1237,5 +1003,128 @@ def multi_linechart(df_line, sett): color=label_colour, fontsize=label_size ) - + return fig, ax + def multi_linechart_test(data, ylab, xlab, **kwargs): + ''' + Creates a line chart of one or more lines. + Number of lines to plot determined from columns in input dataframe. + 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 + Should include this if ymin < 0. + yinc : int, optional + The increment of ticks on the y axis. + axis : Axes object, optional + The axis that the plot will be located on. + plot_size : tuple, optional + set_plot_size : bool, optional + + Returns + -------- + fig + Matplotlib fig object + ax + Matplotlib ax object + ''' + + func() + + ymin, ymax, yinc = calculate_y_params(data, **kwargs) + + fig, ax = plot_line_data(data, kwargs.get('ax',None)) + + fig, ax = set_plot_style(fig, ax, ymin, ymax, + plot_size=kwargs.get('plot_size', (6.1, 4.1)), + set_plot_size=kwargs.get('set_plot_size', True)) + + fig, ax = set_ticks(fig, ax, ymin, ymax, yinc) + + fig, ax = set_labels(fig, ax, xlab, ylab) + + return fig, ax + +def calculate_y_params(df, **kwargs): + ''' + Checks if minimum, maximum and increment values are passed into the plotting function + for the y axis, and returns these. Otherwise, calculates them. + ''' + ymax = kwargs.get('ymax', int(df.max(axis=1).max(axis=0))) + ymin = kwargs.get('ymin', 0) + delta, i = calculate_delta(ymax, ymin) + yinc = kwargs.get('yinc', int(round(delta+1)*pow(10,i))) + + return ymin, ymax, yinc + +def calculate_delta(ymax, ymin): + ''' + Returns parameters used to find the size of the y axis increments. + ''' + delta = (ymax - ymin)/4 + i = 0 + while True: + delta /= 10 + i += 1 + if delta < 10: + break + return delta, i + +def plot_line_data(df, axis): + ''' + Plots all columns in the input dataframe as lines in one graph. + ''' + if axis != None: + ax = axis + fig = ax.get_figure() + else: + fig, ax = plt.subplots() + + colour_instance = colour() + for i, col in enumerate(df.columns): + hex_code = colour_instance.get_colour_from_index(i+1) + ax.plot(df[col] ,linewidth=3, color = hex_code) + + return fig, ax + +def set_plot_style(fig, ax, ymin, ymax, plot_size, set_plot_size): + ''' + Sets background and grid colour for plot. + ''' + if set_plot_size == True: + fig.set_size_inches(plot_size) + ax.set_facecolor('xkcd:white') + ax.set_ylim([ymin, ymax]) + ax.grid(color='k', linestyle='-', linewidth=0.2) + return fig, ax + +def set_ticks(fig, ax, ymin, ymax, yinc): + ''' + Sets x and y axis tick locations and tick labels. + ''' + ax.yaxis.set_major_formatter(mpl.ticker.StrMethodFormatter('{x:,.0f}')) + ax.xaxis.set_major_locator(mpl.ticker.FixedLocator(range(len(ax.get_xticklabels())))) + ax.set_xticklabels(labels=ax.get_xticklabels(), fontsize = 9, fontname=font.normal) + ax.set_yticks(range(ymin, ymax + yinc, yinc), labels=range(ymin, ymax + yinc, yinc), fontsize = 9, fontname = font.normal) + + return fig, ax + +def set_labels(fig, ax, xlab, ylab): + ''' + Set the labels of the y and x axes. + ''' + ax.set_xlabel(xlab, fontsize=9, fontweight = 'bold', horizontalalignment='right', x=0, labelpad=10, + fontname = font.normal) + ax.set_ylabel(ylab, fontsize=9, fontweight = 'bold', + horizontalalignment='right', y=1.0, + labelpad=10, fontname = font.normal) + + return fig, ax \ No newline at end of file