Python--matplotlib Drawing visualization practiced hand--line chart/bar chart

Recently learn matplotlib mapping visualization, feel more knowledge points, while learning side record.

For data visualization, personal advice jupyter Notebook.

1. First guide the package, set the environment

import pandas as pdimport numpy as npimport sysreload(sys)sys.setdefaultencoding(‘utf-8‘)import matplotlib.pyplot as plt%matplotlib inline #使图片内嵌交互环境显示plt.rcParams[‘font.sans-serif‘]=[‘SimHei‘] #用来正常显示中文标签plt.rcParams[‘axes.unicode_minus‘]=False #用来正常显示负号

2. Read the data and display

data_every_month = pd.read_csv(‘data_every_month.txt‘)data_every_month

3. Draw a Line chart

y = data_every_month[‘nums‘].T.valuesx = range(0,len(y))plt.figure(figsize=(10, 6))plt.plot(x,y,‘‘)  plt.xticks((0,20,40,60,80,100,120),(‘200504‘,‘200912‘,‘201108‘,‘201306‘,‘201502‘,‘201610‘,‘‘))plt.xlabel(‘年月‘)plt.ylabel(‘XX事件数‘)plt.title(‘每月XX事件数‘)plt.show()

4. Take the fragment data, the same picture two lines to distinguish

y1=y[79:91]y2=y[91:102]x1=range(0,len(y1))x2=range(0,len(y2))plt.figure(figsize=(10, 6))plt.plot(x1,y1,‘‘,label="2015年")plt.plot(x2,y2,‘‘,label="2016年")plt.title(‘2015-2016年月XX事件数‘)plt.legend(loc=‘upper right‘)plt.xticks((0,2,4,6,8,10),(‘1月‘,‘3月‘,‘5月‘,‘7月‘,‘9月‘,‘11月‘))plt.xlabel(‘月份‘)plt.ylabel(‘XX事件数‘)plt.grid(x1)plt.show()

5. Read the hourly frequency data, draw the overlapping bar chart

data_hour2015 = pd.read_csv(‘data_hour2015.txt‘)data_hour2016 = pd.read_csv(‘data_hour2016.txt‘)plt.figure(figsize=(10, 6))data_hour2015[‘nums‘].T.plot.bar(color=‘g‘,alpha=0.6,label=‘2015年‘)data_hour2016[‘nums‘].T.plot.bar(color=‘r‘,alpha=0.4,label=‘2016年‘)plt.xlabel(‘小时‘)plt.ylabel(‘XX事件数量‘)plt.title(‘XX事件数小时分布‘)plt.legend(loc=‘upper right‘)plt.show()

6. Read Zhou Pin Number data, draw non-overlapping bar chart

data_week2015 = pd.read_csv(‘data_week2015.txt‘)[‘nums‘].T.valuesdata_week2016 = pd.read_csv(‘data_week2016.txt‘)[‘nums‘].T.valuesplt.figure(figsize=(10, 6))xweek=range(0,len(data_week2015))xweek1=[i+0.3 for i in xweek]plt.bar(xweek,data_week2015,color=‘g‘,width = .3,alpha=0.6,label=‘2015年‘)plt.bar(xweek1,data_week2016,color=‘r‘,width = .3,alpha=0.4,label=‘2016年‘)plt.xlabel(‘周‘)plt.ylabel(‘XX事件数量‘)plt.title(‘XX事件数周分布‘)plt.legend(loc=‘upper right‘)plt.xticks(range(0,7),[‘星期日‘,‘星期一‘,‘星期二‘,‘星期三‘,‘星期四‘,‘星期五‘,‘星期六‘])plt.show()

7. Read category frequency data draw horizontal bar chart

data_bar = pd.read_csv(‘data_bar.txt‘)label = data_bar[‘wfxw‘].T.valuesxtop = data_bar[‘nums‘].T.valuesidx = np.arange(len(xtop))fig = plt.figure(figsize=(12,12))plt.barh(idx, xtop, color=‘b‘,alpha=0.6)plt.yticks(idx+0.4,label)plt.grid(axis=‘x‘)plt.xlabel(‘XX事件次数‘)plt.ylabel(‘XX事件名称‘)plt.title(‘2015.1-2016.11月XX事件排行榜‘)plt.show()

Python--matplotlib Drawing visualization practiced hand--line chart/bar chart