diff --git a/open-machine-learning-jupyter-book/data-science/working-with-data/data-preparation.ipynb b/open-machine-learning-jupyter-book/data-science/working-with-data/data-preparation.ipynb index 2db2d17e4d..5ef5816e59 100644 --- a/open-machine-learning-jupyter-book/data-science/working-with-data/data-preparation.ipynb +++ b/open-machine-learning-jupyter-book/data-science/working-with-data/data-preparation.ipynb @@ -2,9 +2,8 @@ "cells": [ { "cell_type": "code", - "execution_count": 21, + "execution_count": 1, "metadata": { - "editable": true, "slideshow": { "slide_type": "" }, @@ -24,7 +23,6 @@ { "cell_type": "markdown", "metadata": { - "editable": true, "slideshow": { "slide_type": "" }, @@ -48,7 +46,6 @@ { "cell_type": "markdown", "metadata": { - "editable": true, "slideshow": { "slide_type": "" }, @@ -100,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -113,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -149,7 +146,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -228,7 +225,7 @@ "4 5.0 3.6 1.4 0.2" ] }, - "execution_count": 24, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -246,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -325,7 +322,7 @@ "149 5.9 3.0 5.1 1.8" ] }, - "execution_count": 25, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -366,7 +363,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -379,7 +376,7 @@ "dtype: bool" ] }, - "execution_count": 26, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -406,7 +403,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -417,7 +414,7 @@ "dtype: object" ] }, - "execution_count": 27, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -438,7 +435,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -497,7 +494,7 @@ "2 NaN 6.0 9" ] }, - "execution_count": 28, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -520,7 +517,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -565,7 +562,7 @@ "1 2.0 5.0 8" ] }, - "execution_count": 29, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -583,7 +580,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -634,7 +631,7 @@ "2 9" ] }, - "execution_count": 30, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -654,7 +651,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -717,7 +714,7 @@ "2 NaN 6.0 9 NaN" ] }, - "execution_count": 31, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -736,7 +733,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -783,7 +780,7 @@ "1 2.0 5.0 8 NaN" ] }, - "execution_count": 32, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -803,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -817,7 +814,7 @@ "dtype: float64" ] }, - "execution_count": 33, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -836,7 +833,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -850,7 +847,7 @@ "dtype: float64" ] }, - "execution_count": 34, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -868,17 +865,9 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 15, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\yienk\\AppData\\Local\\Temp\\ipykernel_12784\\2319704702.py:1: FutureWarning: DataFrame.fillna with 'method' is deprecated and will raise in a future version. Use obj.ffill() or obj.bfill() instead.\n", - " example2.fillna(method='ffill', axis=1)\n" - ] - }, { "data": { "text/html": [ @@ -939,7 +928,7 @@ "2 NaN 6.0 9.0 9.0" ] }, - "execution_count": 35, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -975,7 +964,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -1042,7 +1031,7 @@ "4 B 3" ] }, - "execution_count": 36, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1055,7 +1044,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -1069,7 +1058,7 @@ "dtype: bool" ] }, - "execution_count": 37, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -1087,7 +1076,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -1142,7 +1131,7 @@ "3 B 3" ] }, - "execution_count": 38, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -1160,7 +1149,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1209,7 +1198,7 @@ "1 B 2" ] }, - "execution_count": 39, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -1262,7 +1251,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.13" + "version": "3.9.18" } }, "nbformat": 4,