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Andre-Tan/2024Mar31 - Pandas Styling.ipynb

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Short Notes on Possibilities in Pandas Table Visualization
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2024Mar31 - Pandas Styling.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "e6a4cec5",
"metadata": {
"toc": true
},
"source": [
"<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
"<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#CSS-Properties-and-String-Formats\" data-toc-modified-id=\"CSS-Properties-and-String-Formats-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>CSS Properties and String Formats</a></span></li><li><span><a href=\"#Built-in-Highlighters\" data-toc-modified-id=\"Built-in-Highlighters-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Built-in Highlighters</a></span></li><li><span><a href=\"#Custom-Highlighters\" data-toc-modified-id=\"Custom-Highlighters-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Custom Highlighters</a></span></li><li><span><a href=\"#Set-Index-or-Columns-Sticky-to-Display\" data-toc-modified-id=\"Set-Index-or-Columns-Sticky-to-Display-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Set Index or Columns Sticky to Display</a></span></li><li><span><a href=\"#References\" data-toc-modified-id=\"References-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>References</a></span></li></ul></div>"
]
},
{
"cell_type": "markdown",
"id": "2199d950",
"metadata": {},
"source": [
"**Note:** Open the notebook in [this NBViewer link](https://nbviewer.org/gist/Andre-Tan/970993febfb0222b3e40f05fdd948674) to display the notebook properly."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "3581c01b",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.294215Z",
"start_time": "2024-03-31T11:40:40.552830Z"
}
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import datetime as dt"
]
},
{
"cell_type": "markdown",
"id": "b42c0ca5",
"metadata": {},
"source": [
"# CSS Properties and String Formats"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d8c49456",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.310172Z",
"start_time": "2024-03-31T11:40:41.298204Z"
}
},
"outputs": [],
"source": [
"dict_props = { \n",
" 'text-align': 'center', # Justify center the values in the DataFrame\n",
" 'font-weight': 'normal', # Can 'bold' the fonts\n",
" 'font-style': 'normal', # Can 'italic' the fonts\n",
" 'color': 'white', # Font color\n",
" 'background-color': 'dimgrey' # Background color\n",
"}\n",
"\n",
"dict_str_formats = {\n",
" \"date\": \"{:%b %Y}\", # Read the section on Datetime format code\n",
" \"float\": \"{:,.2f}\", # Add comma to float, with a precision of 2\n",
" \"percent\": \"{:.2%}\", # Add percent to float, with a precision of 2\n",
" \"text\": lambda x: x.upper() # Can throw a function to the styler\n",
"}"
]
},
{
"cell_type": "markdown",
"id": "c0d87c8c",
"metadata": {},
"source": [
"The `color` argument can take [hex color codes](https://htmlcolorcodes.com/) or [CSS colors in this Matplotlib link](https://matplotlib.org/stable/gallery/color/named_colors.html)\n",
"\n",
"---\n",
"\n",
"The Python documentation for the [datetime library format codes](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes) shows us a list for `strftime()` and `strptime()`. To make things easier, a couple of common directives to use are:\n",
"\n",
"| Directive | Meaning | Example |\n",
"|----|----|----|\n",
"|`%a`| Weekday as locale's abbreviated name | Sun, Mon, Sat |\n",
"|`%A`| Weekday as locale's full name | Sunday, Monday, Saturday |\n",
"|`%w`| Weekday as a decimal number, where 0 is Sunday and 6 is Saturday | 0,1,2...6 |\n",
"|`%b`| Month as locale's abbreviated name | Jan, Feb, Dec |\n",
"|`%B`| Month as locale's full name | January, February, December |\n",
"|`%m`| Month as a zero-padded decimal number | 01, 02, 12 |\n",
"|`%y`| Year without century as a zero-padded decimal number | 01, 99 |\n",
"|`%Y`| Year with century as decimal number | 2013, 2023, 2024 |\n",
"|`%z`| UTC offset in the form of time offset (empty string if the object is naive) | +0000, +0800, -0400 |\n",
"|`%Z`| Time zone name (empty string if the object is naive) | UTC, GMT |\n",
"|`%c`| Locale's appropriate date and time representation | Tue Aug 16 21:30:00 1988 |\n",
"|`%x`| Locale's appropriate date representation | 08/16/1988 |\n",
"|`%X`| Locale's appropriate time representation | 21:30:00 |"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e463b29a",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.837211Z",
"start_time": "2024-03-31T11:40:41.312167Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>float</th>\n",
" <th>percent</th>\n",
" <th>text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2024-03-31</td>\n",
" <td>20000.000</td>\n",
" <td>NaN</td>\n",
" <td>here</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2023-02-01</td>\n",
" <td>1000.245</td>\n",
" <td>0.314567</td>\n",
" <td>there</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2022-01-01</td>\n",
" <td>500000.000</td>\n",
" <td>1.000000</td>\n",
" <td>everywhere</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date float percent text\n",
"0 2024-03-31 20000.000 NaN here\n",
"1 2023-02-01 1000.245 0.314567 there\n",
"2 2022-01-01 500000.000 1.000000 everywhere"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_d4277_ th {\n",
" text-align: center;\n",
"}\n",
"#T_d4277_row0_col0, #T_d4277_row0_col1, #T_d4277_row0_col2, #T_d4277_row0_col3, #T_d4277_row1_col0, #T_d4277_row1_col1, #T_d4277_row1_col2, #T_d4277_row1_col3, #T_d4277_row2_col0, #T_d4277_row2_col1, #T_d4277_row2_col2, #T_d4277_row2_col3 {\n",
" text-align: center;\n",
" font-weight: normal;\n",
" font-style: normal;\n",
" color: white;\n",
" background-color: dimgrey;\n",
"}\n",
"</style>\n",
"<table id=\"T_d4277_\">\n",
" <caption>Example Data <br> Stylized</caption>\n",
" <thead>\n",
" <tr>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td id=\"T_d4277_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_d4277_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_d4277_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_d4277_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <td id=\"T_d4277_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_d4277_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_d4277_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_d4277_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <td id=\"T_d4277_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_d4277_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_d4277_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_d4277_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185aa6ece88>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = pd.DataFrame({\n",
" \"date\": [dt.datetime(2024, 3, 31), dt.datetime(2023, 2, 1), dt.datetime(2022, 1, 1)],\n",
" \"float\": [20000, 1000.245, 500000],\n",
" \"percent\": [np.nan, 0.314567, 1.0],\n",
" \"text\": [\"here\", \"there\", \"everywhere\"]\n",
"})\n",
"\n",
"display(df)\n",
"\n",
"df.style\\\n",
".hide_index()\\\n",
".set_properties(**dict_props)\\\n",
".format(dict_str_formats)\\\n",
".set_caption('Example Data <br> Stylized')\\\n",
".set_table_styles([dict(selector='th', props=[('text-align', 'center')])]) \n",
"# Justify center the column names in the DataFrame"
]
},
{
"cell_type": "markdown",
"id": "8731aadd",
"metadata": {},
"source": [
"# Built-in Highlighters"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "d356aa8d",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.867139Z",
"start_time": "2024-03-31T11:40:41.839207Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_7eb87_row0_col1 {\n",
" background-color: #f0f6fd;\n",
" color: #000000;\n",
"}\n",
"#T_7eb87_row1_col1 {\n",
" background-color: #f7fbff;\n",
" color: #000000;\n",
"}\n",
"#T_7eb87_row1_col2 {\n",
" width: 10em;\n",
" height: 80%;\n",
" background: linear-gradient(90deg,salmon 31.5%, transparent 31.5%);\n",
"}\n",
"#T_7eb87_row2_col1 {\n",
" background-color: #08306b;\n",
" color: #f1f1f1;\n",
"}\n",
"#T_7eb87_row2_col2 {\n",
" width: 10em;\n",
" height: 80%;\n",
" background: linear-gradient(90deg,salmon 100.0%, transparent 100.0%);\n",
"}\n",
"</style>\n",
"<table id=\"T_7eb87_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_7eb87_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_7eb87_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_7eb87_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_7eb87_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_7eb87_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_7eb87_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_7eb87_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_7eb87_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_7eb87_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_7eb87_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_7eb87_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_7eb87_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_7eb87_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_7eb87_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_7eb87_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185aa6e9e48>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style\\\n",
".format(dict_str_formats)\\\n",
".background_gradient(cmap=\"Blues\", subset=[\"float\"])\\\n",
".bar(color=\"salmon\", vmin=0, vmax=1, align='left', subset=[\"percent\"]) # can align zero"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "9bef4287",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.899053Z",
"start_time": "2024-03-31T11:40:41.869132Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_ed4d6_row0_col2 {\n",
" background-color: black;\n",
"}\n",
"#T_ed4d6_row1_col1 {\n",
" background-color: yellow;\n",
"}\n",
"#T_ed4d6_row1_col2 {\n",
" color: blue;\n",
"}\n",
"#T_ed4d6_row2_col2 {\n",
" color: red;\n",
"}\n",
"</style>\n",
"<table id=\"T_ed4d6_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_ed4d6_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_ed4d6_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_ed4d6_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_ed4d6_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_ed4d6_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_ed4d6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_ed4d6_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_ed4d6_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_ed4d6_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_ed4d6_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_ed4d6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_ed4d6_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_ed4d6_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_ed4d6_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_ed4d6_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185aa6ec348>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.style\\\n",
".format(dict_str_formats)\\\n",
".highlight_between(left=0, right=5000, axis=0, props=\"background-color: yellow\", subset=[\"float\"])\\\n",
".highlight_min(axis=0, props=\"color: blue\", subset=[\"percent\"])\\\n",
".highlight_max(axis=0, props=\"color: red\", subset=[\"percent\"])\\\n",
".highlight_null(\"black\")"
]
},
{
"cell_type": "markdown",
"id": "cc28458f",
"metadata": {},
"source": [
"# Custom Highlighters\n",
"\n",
"These can be used on values (with `applymap`) or on series (with `apply` and axis)."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "106b35d8",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:40:41.945927Z",
"start_time": "2024-03-31T11:40:41.901048Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_6273a_row0_col2 {\n",
" background-color: red;\n",
"}\n",
"</style>\n",
"<table id=\"T_6273a_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_6273a_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_6273a_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_6273a_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_6273a_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_6273a_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_6273a_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_6273a_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_6273a_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_6273a_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_6273a_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_6273a_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_6273a_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_6273a_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_6273a_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_6273a_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185ab75c088>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_dc392_row2_col1 {\n",
" background-color: red;\n",
"}\n",
"</style>\n",
"<table id=\"T_dc392_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_dc392_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_dc392_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_dc392_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_dc392_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_dc392_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_dc392_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_dc392_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_dc392_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_dc392_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_dc392_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_dc392_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_dc392_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_dc392_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_dc392_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_dc392_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185aa6e9288>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_bae8f_row0_col0, #T_bae8f_row0_col1, #T_bae8f_row0_col2, #T_bae8f_row0_col3 {\n",
" background-color: yellow;\n",
"}\n",
"</style>\n",
"<table id=\"T_bae8f_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >date</th>\n",
" <th class=\"col_heading level0 col1\" >float</th>\n",
" <th class=\"col_heading level0 col2\" >percent</th>\n",
" <th class=\"col_heading level0 col3\" >text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_bae8f_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
" <td id=\"T_bae8f_row0_col0\" class=\"data row0 col0\" >Mar 2024</td>\n",
" <td id=\"T_bae8f_row0_col1\" class=\"data row0 col1\" >20,000.00</td>\n",
" <td id=\"T_bae8f_row0_col2\" class=\"data row0 col2\" >nan%</td>\n",
" <td id=\"T_bae8f_row0_col3\" class=\"data row0 col3\" >HERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_bae8f_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_bae8f_row1_col0\" class=\"data row1 col0\" >Feb 2023</td>\n",
" <td id=\"T_bae8f_row1_col1\" class=\"data row1 col1\" >1,000.25</td>\n",
" <td id=\"T_bae8f_row1_col2\" class=\"data row1 col2\" >31.46%</td>\n",
" <td id=\"T_bae8f_row1_col3\" class=\"data row1 col3\" >THERE</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_bae8f_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_bae8f_row2_col0\" class=\"data row2 col0\" >Jan 2022</td>\n",
" <td id=\"T_bae8f_row2_col1\" class=\"data row2 col1\" >500,000.00</td>\n",
" <td id=\"T_bae8f_row2_col2\" class=\"data row2 col2\" >100.00%</td>\n",
" <td id=\"T_bae8f_row2_col3\" class=\"data row2 col3\" >EVERYWHERE</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185ab715b88>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def style_null(value, props=''):\n",
" return props if pd.isnull(value) else None\n",
"\n",
"def highlight_max(series, props=''):\n",
" return [props if value == series.max() else '' for value in series]\n",
"\n",
"def highlight_row_text(series, text, props=''):\n",
" if text in series.values:\n",
" return [props] * len(series.values)\n",
" else:\n",
" return ''\n",
"\n",
"display(\n",
" df.style\\\n",
" .format(dict_str_formats)\\\n",
" .applymap(style_null, props='background-color: red', subset=['percent'])\n",
")\n",
" \n",
"display(\n",
" df.style\\\n",
" .format(dict_str_formats)\\\n",
" .apply(highlight_max, props='background-color: red', subset=['float'], axis=0)\n",
")\n",
"\n",
"display(\n",
" df.style\\\n",
" .format(dict_str_formats)\\\n",
" .apply(highlight_row_text, text=\"here\", props='background-color: yellow', axis=1)\n",
")"
]
},
{
"cell_type": "markdown",
"id": "e04a8299",
"metadata": {},
"source": [
"# Set Index or Columns Sticky to Display\n",
"\n",
"The method `set_sticky` causes either the `index` or `columns` to be sticky to the display. This lets you see them even if you scroll far."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "4a0c5ba8",
"metadata": {
"ExecuteTime": {
"end_time": "2024-03-31T11:44:57.294389Z",
"start_time": "2024-03-31T11:44:57.205550Z"
},
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<style type=\"text/css\">\n",
"#T_685d7_ thead tr:nth-child(1) th {\n",
" position: sticky;\n",
" background-color: white;\n",
" top: 0px;\n",
" z-index: 2;\n",
"}\n",
"</style>\n",
"<table id=\"T_685d7_\">\n",
" <thead>\n",
" <tr>\n",
" <th class=\"blank level0\" >&nbsp;</th>\n",
" <th class=\"col_heading level0 col0\" >PassengerId</th>\n",
" <th class=\"col_heading level0 col1\" >Survived</th>\n",
" <th class=\"col_heading level0 col2\" >Pclass</th>\n",
" <th class=\"col_heading level0 col3\" >Name</th>\n",
" <th class=\"col_heading level0 col4\" >Sex</th>\n",
" <th class=\"col_heading level0 col5\" >Age</th>\n",
" <th class=\"col_heading level0 col6\" >SibSp</th>\n",
" <th class=\"col_heading level0 col7\" >Parch</th>\n",
" <th class=\"col_heading level0 col8\" >Ticket</th>\n",
" <th class=\"col_heading level0 col9\" >Fare</th>\n",
" <th class=\"col_heading level0 col10\" >Cabin</th>\n",
" <th class=\"col_heading level0 col11\" >Embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row0\" class=\"row_heading level0 row0\" >222</th>\n",
" <td id=\"T_685d7_row0_col0\" class=\"data row0 col0\" >223</td>\n",
" <td id=\"T_685d7_row0_col1\" class=\"data row0 col1\" >0</td>\n",
" <td id=\"T_685d7_row0_col2\" class=\"data row0 col2\" >3</td>\n",
" <td id=\"T_685d7_row0_col3\" class=\"data row0 col3\" >Green, Mr. George Henry</td>\n",
" <td id=\"T_685d7_row0_col4\" class=\"data row0 col4\" >male</td>\n",
" <td id=\"T_685d7_row0_col5\" class=\"data row0 col5\" >51.000000</td>\n",
" <td id=\"T_685d7_row0_col6\" class=\"data row0 col6\" >0</td>\n",
" <td id=\"T_685d7_row0_col7\" class=\"data row0 col7\" >0</td>\n",
" <td id=\"T_685d7_row0_col8\" class=\"data row0 col8\" >21440</td>\n",
" <td id=\"T_685d7_row0_col9\" class=\"data row0 col9\" >8.050000</td>\n",
" <td id=\"T_685d7_row0_col10\" class=\"data row0 col10\" >nan</td>\n",
" <td id=\"T_685d7_row0_col11\" class=\"data row0 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row1\" class=\"row_heading level0 row1\" >130</th>\n",
" <td id=\"T_685d7_row1_col0\" class=\"data row1 col0\" >131</td>\n",
" <td id=\"T_685d7_row1_col1\" class=\"data row1 col1\" >0</td>\n",
" <td id=\"T_685d7_row1_col2\" class=\"data row1 col2\" >3</td>\n",
" <td id=\"T_685d7_row1_col3\" class=\"data row1 col3\" >Drazenoic, Mr. Jozef</td>\n",
" <td id=\"T_685d7_row1_col4\" class=\"data row1 col4\" >male</td>\n",
" <td id=\"T_685d7_row1_col5\" class=\"data row1 col5\" >33.000000</td>\n",
" <td id=\"T_685d7_row1_col6\" class=\"data row1 col6\" >0</td>\n",
" <td id=\"T_685d7_row1_col7\" class=\"data row1 col7\" >0</td>\n",
" <td id=\"T_685d7_row1_col8\" class=\"data row1 col8\" >349241</td>\n",
" <td id=\"T_685d7_row1_col9\" class=\"data row1 col9\" >7.895800</td>\n",
" <td id=\"T_685d7_row1_col10\" class=\"data row1 col10\" >nan</td>\n",
" <td id=\"T_685d7_row1_col11\" class=\"data row1 col11\" >C</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row2\" class=\"row_heading level0 row2\" >614</th>\n",
" <td id=\"T_685d7_row2_col0\" class=\"data row2 col0\" >615</td>\n",
" <td id=\"T_685d7_row2_col1\" class=\"data row2 col1\" >0</td>\n",
" <td id=\"T_685d7_row2_col2\" class=\"data row2 col2\" >3</td>\n",
" <td id=\"T_685d7_row2_col3\" class=\"data row2 col3\" >Brocklebank, Mr. William Alfred</td>\n",
" <td id=\"T_685d7_row2_col4\" class=\"data row2 col4\" >male</td>\n",
" <td id=\"T_685d7_row2_col5\" class=\"data row2 col5\" >35.000000</td>\n",
" <td id=\"T_685d7_row2_col6\" class=\"data row2 col6\" >0</td>\n",
" <td id=\"T_685d7_row2_col7\" class=\"data row2 col7\" >0</td>\n",
" <td id=\"T_685d7_row2_col8\" class=\"data row2 col8\" >364512</td>\n",
" <td id=\"T_685d7_row2_col9\" class=\"data row2 col9\" >8.050000</td>\n",
" <td id=\"T_685d7_row2_col10\" class=\"data row2 col10\" >nan</td>\n",
" <td id=\"T_685d7_row2_col11\" class=\"data row2 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row3\" class=\"row_heading level0 row3\" >595</th>\n",
" <td id=\"T_685d7_row3_col0\" class=\"data row3 col0\" >596</td>\n",
" <td id=\"T_685d7_row3_col1\" class=\"data row3 col1\" >0</td>\n",
" <td id=\"T_685d7_row3_col2\" class=\"data row3 col2\" >3</td>\n",
" <td id=\"T_685d7_row3_col3\" class=\"data row3 col3\" >Van Impe, Mr. Jean Baptiste</td>\n",
" <td id=\"T_685d7_row3_col4\" class=\"data row3 col4\" >male</td>\n",
" <td id=\"T_685d7_row3_col5\" class=\"data row3 col5\" >36.000000</td>\n",
" <td id=\"T_685d7_row3_col6\" class=\"data row3 col6\" >1</td>\n",
" <td id=\"T_685d7_row3_col7\" class=\"data row3 col7\" >1</td>\n",
" <td id=\"T_685d7_row3_col8\" class=\"data row3 col8\" >345773</td>\n",
" <td id=\"T_685d7_row3_col9\" class=\"data row3 col9\" >24.150000</td>\n",
" <td id=\"T_685d7_row3_col10\" class=\"data row3 col10\" >nan</td>\n",
" <td id=\"T_685d7_row3_col11\" class=\"data row3 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row4\" class=\"row_heading level0 row4\" >818</th>\n",
" <td id=\"T_685d7_row4_col0\" class=\"data row4 col0\" >819</td>\n",
" <td id=\"T_685d7_row4_col1\" class=\"data row4 col1\" >0</td>\n",
" <td id=\"T_685d7_row4_col2\" class=\"data row4 col2\" >3</td>\n",
" <td id=\"T_685d7_row4_col3\" class=\"data row4 col3\" >Holm, Mr. John Fredrik Alexander</td>\n",
" <td id=\"T_685d7_row4_col4\" class=\"data row4 col4\" >male</td>\n",
" <td id=\"T_685d7_row4_col5\" class=\"data row4 col5\" >43.000000</td>\n",
" <td id=\"T_685d7_row4_col6\" class=\"data row4 col6\" >0</td>\n",
" <td id=\"T_685d7_row4_col7\" class=\"data row4 col7\" >0</td>\n",
" <td id=\"T_685d7_row4_col8\" class=\"data row4 col8\" >C 7075</td>\n",
" <td id=\"T_685d7_row4_col9\" class=\"data row4 col9\" >6.450000</td>\n",
" <td id=\"T_685d7_row4_col10\" class=\"data row4 col10\" >nan</td>\n",
" <td id=\"T_685d7_row4_col11\" class=\"data row4 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row5\" class=\"row_heading level0 row5\" >583</th>\n",
" <td id=\"T_685d7_row5_col0\" class=\"data row5 col0\" >584</td>\n",
" <td id=\"T_685d7_row5_col1\" class=\"data row5 col1\" >0</td>\n",
" <td id=\"T_685d7_row5_col2\" class=\"data row5 col2\" >1</td>\n",
" <td id=\"T_685d7_row5_col3\" class=\"data row5 col3\" >Ross, Mr. John Hugo</td>\n",
" <td id=\"T_685d7_row5_col4\" class=\"data row5 col4\" >male</td>\n",
" <td id=\"T_685d7_row5_col5\" class=\"data row5 col5\" >36.000000</td>\n",
" <td id=\"T_685d7_row5_col6\" class=\"data row5 col6\" >0</td>\n",
" <td id=\"T_685d7_row5_col7\" class=\"data row5 col7\" >0</td>\n",
" <td id=\"T_685d7_row5_col8\" class=\"data row5 col8\" >13049</td>\n",
" <td id=\"T_685d7_row5_col9\" class=\"data row5 col9\" >40.125000</td>\n",
" <td id=\"T_685d7_row5_col10\" class=\"data row5 col10\" >A10</td>\n",
" <td id=\"T_685d7_row5_col11\" class=\"data row5 col11\" >C</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row6\" class=\"row_heading level0 row6\" >138</th>\n",
" <td id=\"T_685d7_row6_col0\" class=\"data row6 col0\" >139</td>\n",
" <td id=\"T_685d7_row6_col1\" class=\"data row6 col1\" >0</td>\n",
" <td id=\"T_685d7_row6_col2\" class=\"data row6 col2\" >3</td>\n",
" <td id=\"T_685d7_row6_col3\" class=\"data row6 col3\" >Osen, Mr. Olaf Elon</td>\n",
" <td id=\"T_685d7_row6_col4\" class=\"data row6 col4\" >male</td>\n",
" <td id=\"T_685d7_row6_col5\" class=\"data row6 col5\" >16.000000</td>\n",
" <td id=\"T_685d7_row6_col6\" class=\"data row6 col6\" >0</td>\n",
" <td id=\"T_685d7_row6_col7\" class=\"data row6 col7\" >0</td>\n",
" <td id=\"T_685d7_row6_col8\" class=\"data row6 col8\" >7534</td>\n",
" <td id=\"T_685d7_row6_col9\" class=\"data row6 col9\" >9.216700</td>\n",
" <td id=\"T_685d7_row6_col10\" class=\"data row6 col10\" >nan</td>\n",
" <td id=\"T_685d7_row6_col11\" class=\"data row6 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row7\" class=\"row_heading level0 row7\" >95</th>\n",
" <td id=\"T_685d7_row7_col0\" class=\"data row7 col0\" >96</td>\n",
" <td id=\"T_685d7_row7_col1\" class=\"data row7 col1\" >0</td>\n",
" <td id=\"T_685d7_row7_col2\" class=\"data row7 col2\" >3</td>\n",
" <td id=\"T_685d7_row7_col3\" class=\"data row7 col3\" >Shorney, Mr. Charles Joseph</td>\n",
" <td id=\"T_685d7_row7_col4\" class=\"data row7 col4\" >male</td>\n",
" <td id=\"T_685d7_row7_col5\" class=\"data row7 col5\" >nan</td>\n",
" <td id=\"T_685d7_row7_col6\" class=\"data row7 col6\" >0</td>\n",
" <td id=\"T_685d7_row7_col7\" class=\"data row7 col7\" >0</td>\n",
" <td id=\"T_685d7_row7_col8\" class=\"data row7 col8\" >374910</td>\n",
" <td id=\"T_685d7_row7_col9\" class=\"data row7 col9\" >8.050000</td>\n",
" <td id=\"T_685d7_row7_col10\" class=\"data row7 col10\" >nan</td>\n",
" <td id=\"T_685d7_row7_col11\" class=\"data row7 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row8\" class=\"row_heading level0 row8\" >850</th>\n",
" <td id=\"T_685d7_row8_col0\" class=\"data row8 col0\" >851</td>\n",
" <td id=\"T_685d7_row8_col1\" class=\"data row8 col1\" >0</td>\n",
" <td id=\"T_685d7_row8_col2\" class=\"data row8 col2\" >3</td>\n",
" <td id=\"T_685d7_row8_col3\" class=\"data row8 col3\" >Andersson, Master. Sigvard Harald Elias</td>\n",
" <td id=\"T_685d7_row8_col4\" class=\"data row8 col4\" >male</td>\n",
" <td id=\"T_685d7_row8_col5\" class=\"data row8 col5\" >4.000000</td>\n",
" <td id=\"T_685d7_row8_col6\" class=\"data row8 col6\" >4</td>\n",
" <td id=\"T_685d7_row8_col7\" class=\"data row8 col7\" >2</td>\n",
" <td id=\"T_685d7_row8_col8\" class=\"data row8 col8\" >347082</td>\n",
" <td id=\"T_685d7_row8_col9\" class=\"data row8 col9\" >31.275000</td>\n",
" <td id=\"T_685d7_row8_col10\" class=\"data row8 col10\" >nan</td>\n",
" <td id=\"T_685d7_row8_col11\" class=\"data row8 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row9\" class=\"row_heading level0 row9\" >421</th>\n",
" <td id=\"T_685d7_row9_col0\" class=\"data row9 col0\" >422</td>\n",
" <td id=\"T_685d7_row9_col1\" class=\"data row9 col1\" >0</td>\n",
" <td id=\"T_685d7_row9_col2\" class=\"data row9 col2\" >3</td>\n",
" <td id=\"T_685d7_row9_col3\" class=\"data row9 col3\" >Charters, Mr. David</td>\n",
" <td id=\"T_685d7_row9_col4\" class=\"data row9 col4\" >male</td>\n",
" <td id=\"T_685d7_row9_col5\" class=\"data row9 col5\" >21.000000</td>\n",
" <td id=\"T_685d7_row9_col6\" class=\"data row9 col6\" >0</td>\n",
" <td id=\"T_685d7_row9_col7\" class=\"data row9 col7\" >0</td>\n",
" <td id=\"T_685d7_row9_col8\" class=\"data row9 col8\" >A/5. 13032</td>\n",
" <td id=\"T_685d7_row9_col9\" class=\"data row9 col9\" >7.733300</td>\n",
" <td id=\"T_685d7_row9_col10\" class=\"data row9 col10\" >nan</td>\n",
" <td id=\"T_685d7_row9_col11\" class=\"data row9 col11\" >Q</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row10\" class=\"row_heading level0 row10\" >63</th>\n",
" <td id=\"T_685d7_row10_col0\" class=\"data row10 col0\" >64</td>\n",
" <td id=\"T_685d7_row10_col1\" class=\"data row10 col1\" >0</td>\n",
" <td id=\"T_685d7_row10_col2\" class=\"data row10 col2\" >3</td>\n",
" <td id=\"T_685d7_row10_col3\" class=\"data row10 col3\" >Skoog, Master. Harald</td>\n",
" <td id=\"T_685d7_row10_col4\" class=\"data row10 col4\" >male</td>\n",
" <td id=\"T_685d7_row10_col5\" class=\"data row10 col5\" >4.000000</td>\n",
" <td id=\"T_685d7_row10_col6\" class=\"data row10 col6\" >3</td>\n",
" <td id=\"T_685d7_row10_col7\" class=\"data row10 col7\" >2</td>\n",
" <td id=\"T_685d7_row10_col8\" class=\"data row10 col8\" >347088</td>\n",
" <td id=\"T_685d7_row10_col9\" class=\"data row10 col9\" >27.900000</td>\n",
" <td id=\"T_685d7_row10_col10\" class=\"data row10 col10\" >nan</td>\n",
" <td id=\"T_685d7_row10_col11\" class=\"data row10 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row11\" class=\"row_heading level0 row11\" >357</th>\n",
" <td id=\"T_685d7_row11_col0\" class=\"data row11 col0\" >358</td>\n",
" <td id=\"T_685d7_row11_col1\" class=\"data row11 col1\" >0</td>\n",
" <td id=\"T_685d7_row11_col2\" class=\"data row11 col2\" >2</td>\n",
" <td id=\"T_685d7_row11_col3\" class=\"data row11 col3\" >Funk, Miss. Annie Clemmer</td>\n",
" <td id=\"T_685d7_row11_col4\" class=\"data row11 col4\" >female</td>\n",
" <td id=\"T_685d7_row11_col5\" class=\"data row11 col5\" >38.000000</td>\n",
" <td id=\"T_685d7_row11_col6\" class=\"data row11 col6\" >0</td>\n",
" <td id=\"T_685d7_row11_col7\" class=\"data row11 col7\" >0</td>\n",
" <td id=\"T_685d7_row11_col8\" class=\"data row11 col8\" >237671</td>\n",
" <td id=\"T_685d7_row11_col9\" class=\"data row11 col9\" >13.000000</td>\n",
" <td id=\"T_685d7_row11_col10\" class=\"data row11 col10\" >nan</td>\n",
" <td id=\"T_685d7_row11_col11\" class=\"data row11 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row12\" class=\"row_heading level0 row12\" >560</th>\n",
" <td id=\"T_685d7_row12_col0\" class=\"data row12 col0\" >561</td>\n",
" <td id=\"T_685d7_row12_col1\" class=\"data row12 col1\" >0</td>\n",
" <td id=\"T_685d7_row12_col2\" class=\"data row12 col2\" >3</td>\n",
" <td id=\"T_685d7_row12_col3\" class=\"data row12 col3\" >Morrow, Mr. Thomas Rowan</td>\n",
" <td id=\"T_685d7_row12_col4\" class=\"data row12 col4\" >male</td>\n",
" <td id=\"T_685d7_row12_col5\" class=\"data row12 col5\" >nan</td>\n",
" <td id=\"T_685d7_row12_col6\" class=\"data row12 col6\" >0</td>\n",
" <td id=\"T_685d7_row12_col7\" class=\"data row12 col7\" >0</td>\n",
" <td id=\"T_685d7_row12_col8\" class=\"data row12 col8\" >372622</td>\n",
" <td id=\"T_685d7_row12_col9\" class=\"data row12 col9\" >7.750000</td>\n",
" <td id=\"T_685d7_row12_col10\" class=\"data row12 col10\" >nan</td>\n",
" <td id=\"T_685d7_row12_col11\" class=\"data row12 col11\" >Q</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row13\" class=\"row_heading level0 row13\" >269</th>\n",
" <td id=\"T_685d7_row13_col0\" class=\"data row13 col0\" >270</td>\n",
" <td id=\"T_685d7_row13_col1\" class=\"data row13 col1\" >1</td>\n",
" <td id=\"T_685d7_row13_col2\" class=\"data row13 col2\" >1</td>\n",
" <td id=\"T_685d7_row13_col3\" class=\"data row13 col3\" >Bissette, Miss. Amelia</td>\n",
" <td id=\"T_685d7_row13_col4\" class=\"data row13 col4\" >female</td>\n",
" <td id=\"T_685d7_row13_col5\" class=\"data row13 col5\" >35.000000</td>\n",
" <td id=\"T_685d7_row13_col6\" class=\"data row13 col6\" >0</td>\n",
" <td id=\"T_685d7_row13_col7\" class=\"data row13 col7\" >0</td>\n",
" <td id=\"T_685d7_row13_col8\" class=\"data row13 col8\" >PC 17760</td>\n",
" <td id=\"T_685d7_row13_col9\" class=\"data row13 col9\" >135.633300</td>\n",
" <td id=\"T_685d7_row13_col10\" class=\"data row13 col10\" >C99</td>\n",
" <td id=\"T_685d7_row13_col11\" class=\"data row13 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row14\" class=\"row_heading level0 row14\" >319</th>\n",
" <td id=\"T_685d7_row14_col0\" class=\"data row14 col0\" >320</td>\n",
" <td id=\"T_685d7_row14_col1\" class=\"data row14 col1\" >1</td>\n",
" <td id=\"T_685d7_row14_col2\" class=\"data row14 col2\" >1</td>\n",
" <td id=\"T_685d7_row14_col3\" class=\"data row14 col3\" >Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone)</td>\n",
" <td id=\"T_685d7_row14_col4\" class=\"data row14 col4\" >female</td>\n",
" <td id=\"T_685d7_row14_col5\" class=\"data row14 col5\" >40.000000</td>\n",
" <td id=\"T_685d7_row14_col6\" class=\"data row14 col6\" >1</td>\n",
" <td id=\"T_685d7_row14_col7\" class=\"data row14 col7\" >1</td>\n",
" <td id=\"T_685d7_row14_col8\" class=\"data row14 col8\" >16966</td>\n",
" <td id=\"T_685d7_row14_col9\" class=\"data row14 col9\" >134.500000</td>\n",
" <td id=\"T_685d7_row14_col10\" class=\"data row14 col10\" >E34</td>\n",
" <td id=\"T_685d7_row14_col11\" class=\"data row14 col11\" >C</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row15\" class=\"row_heading level0 row15\" >793</th>\n",
" <td id=\"T_685d7_row15_col0\" class=\"data row15 col0\" >794</td>\n",
" <td id=\"T_685d7_row15_col1\" class=\"data row15 col1\" >0</td>\n",
" <td id=\"T_685d7_row15_col2\" class=\"data row15 col2\" >1</td>\n",
" <td id=\"T_685d7_row15_col3\" class=\"data row15 col3\" >Hoyt, Mr. William Fisher</td>\n",
" <td id=\"T_685d7_row15_col4\" class=\"data row15 col4\" >male</td>\n",
" <td id=\"T_685d7_row15_col5\" class=\"data row15 col5\" >nan</td>\n",
" <td id=\"T_685d7_row15_col6\" class=\"data row15 col6\" >0</td>\n",
" <td id=\"T_685d7_row15_col7\" class=\"data row15 col7\" >0</td>\n",
" <td id=\"T_685d7_row15_col8\" class=\"data row15 col8\" >PC 17600</td>\n",
" <td id=\"T_685d7_row15_col9\" class=\"data row15 col9\" >30.695800</td>\n",
" <td id=\"T_685d7_row15_col10\" class=\"data row15 col10\" >nan</td>\n",
" <td id=\"T_685d7_row15_col11\" class=\"data row15 col11\" >C</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row16\" class=\"row_heading level0 row16\" >430</th>\n",
" <td id=\"T_685d7_row16_col0\" class=\"data row16 col0\" >431</td>\n",
" <td id=\"T_685d7_row16_col1\" class=\"data row16 col1\" >1</td>\n",
" <td id=\"T_685d7_row16_col2\" class=\"data row16 col2\" >1</td>\n",
" <td id=\"T_685d7_row16_col3\" class=\"data row16 col3\" >Bjornstrom-Steffansson, Mr. Mauritz Hakan</td>\n",
" <td id=\"T_685d7_row16_col4\" class=\"data row16 col4\" >male</td>\n",
" <td id=\"T_685d7_row16_col5\" class=\"data row16 col5\" >28.000000</td>\n",
" <td id=\"T_685d7_row16_col6\" class=\"data row16 col6\" >0</td>\n",
" <td id=\"T_685d7_row16_col7\" class=\"data row16 col7\" >0</td>\n",
" <td id=\"T_685d7_row16_col8\" class=\"data row16 col8\" >110564</td>\n",
" <td id=\"T_685d7_row16_col9\" class=\"data row16 col9\" >26.550000</td>\n",
" <td id=\"T_685d7_row16_col10\" class=\"data row16 col10\" >C52</td>\n",
" <td id=\"T_685d7_row16_col11\" class=\"data row16 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row17\" class=\"row_heading level0 row17\" >492</th>\n",
" <td id=\"T_685d7_row17_col0\" class=\"data row17 col0\" >493</td>\n",
" <td id=\"T_685d7_row17_col1\" class=\"data row17 col1\" >0</td>\n",
" <td id=\"T_685d7_row17_col2\" class=\"data row17 col2\" >1</td>\n",
" <td id=\"T_685d7_row17_col3\" class=\"data row17 col3\" >Molson, Mr. Harry Markland</td>\n",
" <td id=\"T_685d7_row17_col4\" class=\"data row17 col4\" >male</td>\n",
" <td id=\"T_685d7_row17_col5\" class=\"data row17 col5\" >55.000000</td>\n",
" <td id=\"T_685d7_row17_col6\" class=\"data row17 col6\" >0</td>\n",
" <td id=\"T_685d7_row17_col7\" class=\"data row17 col7\" >0</td>\n",
" <td id=\"T_685d7_row17_col8\" class=\"data row17 col8\" >113787</td>\n",
" <td id=\"T_685d7_row17_col9\" class=\"data row17 col9\" >30.500000</td>\n",
" <td id=\"T_685d7_row17_col10\" class=\"data row17 col10\" >C30</td>\n",
" <td id=\"T_685d7_row17_col11\" class=\"data row17 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row18\" class=\"row_heading level0 row18\" >860</th>\n",
" <td id=\"T_685d7_row18_col0\" class=\"data row18 col0\" >861</td>\n",
" <td id=\"T_685d7_row18_col1\" class=\"data row18 col1\" >0</td>\n",
" <td id=\"T_685d7_row18_col2\" class=\"data row18 col2\" >3</td>\n",
" <td id=\"T_685d7_row18_col3\" class=\"data row18 col3\" >Hansen, Mr. Claus Peter</td>\n",
" <td id=\"T_685d7_row18_col4\" class=\"data row18 col4\" >male</td>\n",
" <td id=\"T_685d7_row18_col5\" class=\"data row18 col5\" >41.000000</td>\n",
" <td id=\"T_685d7_row18_col6\" class=\"data row18 col6\" >2</td>\n",
" <td id=\"T_685d7_row18_col7\" class=\"data row18 col7\" >0</td>\n",
" <td id=\"T_685d7_row18_col8\" class=\"data row18 col8\" >350026</td>\n",
" <td id=\"T_685d7_row18_col9\" class=\"data row18 col9\" >14.108300</td>\n",
" <td id=\"T_685d7_row18_col10\" class=\"data row18 col10\" >nan</td>\n",
" <td id=\"T_685d7_row18_col11\" class=\"data row18 col11\" >S</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_685d7_level0_row19\" class=\"row_heading level0 row19\" >412</th>\n",
" <td id=\"T_685d7_row19_col0\" class=\"data row19 col0\" >413</td>\n",
" <td id=\"T_685d7_row19_col1\" class=\"data row19 col1\" >1</td>\n",
" <td id=\"T_685d7_row19_col2\" class=\"data row19 col2\" >1</td>\n",
" <td id=\"T_685d7_row19_col3\" class=\"data row19 col3\" >Minahan, Miss. Daisy E</td>\n",
" <td id=\"T_685d7_row19_col4\" class=\"data row19 col4\" >female</td>\n",
" <td id=\"T_685d7_row19_col5\" class=\"data row19 col5\" >33.000000</td>\n",
" <td id=\"T_685d7_row19_col6\" class=\"data row19 col6\" >1</td>\n",
" <td id=\"T_685d7_row19_col7\" class=\"data row19 col7\" >0</td>\n",
" <td id=\"T_685d7_row19_col8\" class=\"data row19 col8\" >19928</td>\n",
" <td id=\"T_685d7_row19_col9\" class=\"data row19 col9\" >90.000000</td>\n",
" <td id=\"T_685d7_row19_col10\" class=\"data row19 col10\" >C78</td>\n",
" <td id=\"T_685d7_row19_col11\" class=\"data row19 col11\" >Q</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x185ab983388>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_titanic = pd.read_csv(\"https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv\")\n",
"\n",
"df_titanic.sample(20).style\\\n",
".set_sticky(axis=\"columns\")"
]
},
{
"cell_type": "markdown",
"id": "f653d56f",
"metadata": {},
"source": [
"# References\n",
"\n",
"1. [Pandas Table Visualization](https://pandas.pydata.org/docs/user_guide/style.html)\n",
"2. [HTML Color Codes](https://htmlcolorcodes.com/)\n",
"3. [Matplotlib's List of Named Colors](https://matplotlib.org/stable/gallery/color/named_colors.html)\n",
"4. [Datetime Strftime Table](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python [conda env:env_catboost]",
"language": "python",
"name": "conda-env-env_catboost-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.11"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": true,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": true,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": false
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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