{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 直方图\n",
"\n",
"```{admonition} 在线刷题\n",
":class: seealso\n",
"\n",
"检查 or 强化 `Pandas` 数据分析操作？👉在线体验「Pandas进阶修炼300题」\n",
"```\n",
"\n",
"```{note} \n",
"本页面代码可以[在线编辑、执行](../指引/在线执行.md)！"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 导入与预设\n",
"\n",
"虽然在 `pandas` 中可以直接调用 `matplotliab` 进行可视化，但是依旧需要进行相关设置，例如字体、精度等。"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"tags": [
"thebe-init"
]
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"plt.rcParams['font.sans-serif'] = ['Songti SC']\n",
"plt.rcParams['axes.unicode_minus']=False"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 默认\n",
"\n",
"重新生成数据 df3 ，并制作直方图"
]
},
{
"cell_type": "code",
"execution_count": 115,
"metadata": {
"tags": [
"hide-input",
"thebe-init"
]
},
"outputs": [],
"source": [
"df3 = pd.DataFrame(\n",
" {\n",
" \"a\": np.random.randn(1000) + 1,\n",
" \"b\": np.random.randn(1000),\n",
" \"c\": np.random.randn(1000) - 1,\n",
" },\n",
" columns=[\"a\", \"b\", \"c\"],\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 118,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 355,
"width": 605
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df3.plot(kind = 'hist', figsize=(10, 6))\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 修改透明度\n",
"\n",
"在上一题的基础上，设置透明度为 0,5"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 355,
"width": 605
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df3.plot(kind = 'hist', figsize=(10, 6),alpha = 0.5)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 修改小区间\n",
"\n",
"在上一题的基础上，堆叠直方图，并设置小区间为20个"
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 355,
"width": 605
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df3.plot(kind = 'hist', figsize=(10, 6),alpha = 0.5,bins = 20,stacked=True)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 拆分子图\n",
"在上一题的基础上，将3个直方图拆分为3个子图"
]
},
{
"cell_type": "code",
"execution_count": 129,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"image/png": {
"height": 370,
"width": 593
},
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df3.diff().hist(alpha=0.5, bins=20, figsize=(10, 6))\n",
"plt.show()"
]
}
],
"metadata": {
"celltoolbar": "Tags",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
},
"toc": {
"base_numbering": 1,
"nav_menu": {},
"number_sections": false,
"sideBar": true,
"skip_h1_title": false,
"title_cell": "Table of Contents",
"title_sidebar": "Contents",
"toc_cell": false,
"toc_position": {},
"toc_section_display": true,
"toc_window_display": true
}
},
"nbformat": 4,
"nbformat_minor": 4
}