{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 散点图的绘制" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# 创建画布\n", "plt.figure(figsize=(20, 8))\n", "\n", "# 绘制图像 散点图\n", "x = [225.98, 247.07, 253.14, 457.85, 241.58, 301.01, 20.67, 288.64,\n", " 163.56, 120.06, 207.83, 342.75, 147.9 , 53.06, 224.72, 29.51,\n", " 21.61, 483.21, 245.25, 399.25, 343.35]\n", "y = [196.63, 203.88, 210.75, 372.74, 202.41, 247.61, 24.9 , 239.34,\n", " 140.32, 104.15, 176.84, 288.23, 128.79, 49.64, 191.74, 33.1 ,\n", " 30.74, 400.02, 205.35, 330.64, 283.45]\n", "plt.scatter(x, y)\n", "\n", "# 显示图像\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 柱状图的绘制" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# 创建画布\n", "plt.figure(figsize=(20,8))\n", "\n", "# 绘制图像 柱状图\n", "movie_names = ['雷神3：诸神黄昏','正义联盟','东方快车谋杀案','寻梦环游记','全球风暴', '降魔传','追捕','七十七天','密战','狂兽','其它']\n", "y = [73853,57767,22354,15969,14839,8725,8716,8318,7916,6764,52222]\n", "x = range(len(movie_names)) \n", "plt.bar(x, y, width=0.5, color=['b','r','g','y','c','m','y','k','c','g','b'])\n", "\n", "# 设置x轴的刻度\n", "plt.xticks(x, movie_names)\n", "\n", "# 显示图像\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "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": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 2 }