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jnothmanjnothman
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Doc tweaks
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‎doc/source/_static/style-excel.png

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‎doc/source/style.ipynb

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@@ -49,7 +49,6 @@
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true,
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"nbsphinx": "hidden"
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},
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"outputs": [],
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.highlight_null().render().split('\\n')[:10]"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"s = df.style.applymap(color_negative_red)\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.apply(highlight_max)"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.\\\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.apply(highlight_max, color='darkorange', axis=None)"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.apply(highlight_max, subset=['B', 'C', 'D'])"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.applymap(color_negative_red,\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.format(\"{:.2%}\")"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.format({'B': \"{:0<4.0f}\", 'D': '{:+.2f}'})"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.format({\"B\": lambda x: \"±{:.2f}\".format(abs(x))})"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.highlight_null(null_color='red')"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"import seaborn as sns\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Uses the full color range\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Compreess the color range\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.bar(subset=['A', 'B'], color='#d65f5f')"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.highlight_max(axis=0)"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.highlight_min(axis=0)"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"outputs": [],
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"source": [
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"df.style.set_properties(**{'background-color': 'black',\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"source": [
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"df2 = -df\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"outputs": [],
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"style2 = df2.style\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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"metadata": {},
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"outputs": [],
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"source": [
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"with pd.option_context('display.precision', 2):\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"metadata": {},
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"df.style\\\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"df.style.set_caption('Colormaps, with a caption.')\\\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from IPython.display import HTML\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"from IPython.html import widgets\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"metadata": {},
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"def magnify():\n",
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{
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"execution_count": null,
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"np.random.seed(25)\n",
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"# Export to Excel\n",
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"\n",
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"*New in version 0.19.0*\n",
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"*New in version 0.20.0*\n",
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"\n",
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"<p style=\"color: red\">*Experimental: This is a new feature and still under development. We'll be adding features and possibly making breaking changes in future releases. We'd love to hear your [feedback](https://github.com/pandas-dev/pandas/issues).*<p style=\"color: red\">\n",
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"\n",
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"df.style.\\\n",
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" applymap(color_negative_red).\\\n",
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" apply(highlight_max).\\\n",
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" to_excel('_static/styled.xlsx', engine='openpyxl')"
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" to_excel('styled.xlsx', engine='openpyxl')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"A screenshot of the output:\n",
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"<a href=\"_static/styled.xlsx\"><img alt=\"Excel spreadsheet with styled DataFrame\" src=\"_static/style-excel.png\"></a>"
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"<img alt=\"Excel spreadsheet with styled DataFrame\" src=\"_static/style-excel.png\">"
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]
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},
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{
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.1"
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"pygments_lexer": "ipython3"
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}
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},
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"nbformat": 4,

‎doc/source/whatsnew/v0.20.0.txt

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.. ipython:: python
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import pandas as pd
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import numpy as np
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np.random.seed(24)
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df = pd.DataFrame({'A': np.linspace(1, 10, 10)})
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df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))],
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df = pd.concat([df, pd.DataFrame(np.random.RandomState(24).randn(10, 4),
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columns=list('BCDE'))],
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axis=1)
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df.iloc[0, 2] = np.nan
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df.style.\
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applymap(color_negative_red).\
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apply(highlight_max).\
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applymap(lambda val: 'color: %s' % 'red' if val < 0 else 'black').\
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apply(lambda s: ['background-color: yellow' if v else ''
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for v in s == s.max()]).\
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to_excel('styled.xlsx', engine='openpyxl')
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.. image:: _static/style-excel.png

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