Data Analysis--graphing (Python)

First, the basic settings

Import the related libraries

Import pandas as Pdimport NumPy as Npimport Matplotlib.pyplot as Pltimport Seaborn as Sns%matplotlib inline   #在ipython总 Show Chart

Chinese is not displayed by default, so you need to change the settings to display Chinese

#显示中文import matplotlib as Mpl mpl.rcparams[' font.sans-serif ') = [u ' simhei ']mpl.rcparams[' axes.unicode_minus '] = False

Setting Global variables

Mpl.rc (' font ', size=12)  #字体mpl. RC (' figure ', figsize= (8,6))  #图像大小mpl. RC (' Axes.spines ', right=false,top= False)  #设置右边上边的横线是否显示

Second, import the data, and view

data = Sns.load_dataset (' tips ') data.head ()
#字段含义分别是: Total consumption, tipping, sex, whether smoking, weekends, time, several people

　

Three, drawing (matplotlib)

1. Line chart

Fig,ax = Plt.subplots ()  #fig主要设置一些全局的变量, and Ax is primarily responsible for drawing ax.plot (data.index,data[' Total_bill ')) fig.set_size_inches ( 12,6) #重新设置大小plt. Title (' Line chart title ', fontsize=22)  #标题, change the font size Ax.set_xlabel (' x axis ', fontsize=18) #设置x轴, the title of the y-axis ax.set_ Ylabel (' Y axis ', fontsize=18) plt.yticks (fontsize=14) #刻度字体大小plt. Xticks (fontsize=14) plt.legend ([' label '],fontsize=15]  #标签内容字体大小plt. Savefig (' Line chart ', dpi=100)  #保存图片, you can set the DPI

2. Column Chart

data_bar1 = data[' Tip '].groupby (data[' Day '). Mean () #统计数据, grouped by week data_bar2 = data[' Tip '].groupby (data[' time '). Mean () #统计数据, grouped by week error = data[' Tip '].groupby (data[' time '). STD () Fig,ax = Plt.subplots (   #画出两个区域ax) [0].bar (data _bar1.index,data_bar1.values)  #第一个区域怎么画ax [0].set_xlabel (' Tip week Diagram ', fontsize=16) ax[0].set_ylabel (' Tip ', FONTSIZE=16) ax[0].legend ([' Week ']) Ax[0].set_ylim (0,4)  #设置Y轴最大最小值ax [1].bar (data_bar2.index,data_bar2.values) # How to draw a second area ax[1].errorbar (data_bar2.index,data_bar2.values,yerr = Error,ls = ' None ', color= ' #96CDCD ', lw=6)  # Add the Variance chart ax[1].legend ([' Lunch and Dinner ']) ax[1].set_xlabel (' Tip dinner diagram ', fontsize=16) ax[1].set_xticklabels ([' Dinner ', ' Luncheon '])   # Change the name of the axis Ax[1].set_ylim (0,4)  #设置Y轴最大最小值fig. Set_size_inches (12,6)  #设置整个图的大小plt. Savefig (' Column chart ', dpi=100)  #保存图片, you can set the DPI

3, the column chart of the horizontal axis

Data_barh = data[' Tip '].groupby (data[' sex '). Mean ()  #统计数据, male and female tip fig,ax = Plt.subplots () Ax.barh (Data_barh.index, data_barh.values,0.4)  #0.4 is width fig.set_size_inches (6,2) plt.title (' Sideways ') ax.set_ylabel (' sex ', fontsize=20) ax.set _xlabel (' tip ', fontsize =) plt.xticks (fontsize=14) ax.set_yticklabels ([' Male ', ' female '])

　　

4. Pie chart

Data_pie = data[' Size '].groupby (data[' size '). Size () Fig,ax = Plt.subplots () ax.pie (data_pir,autopct= '%1.1f%% ', Labels=data_pie.index,colors = [' #B0E0E6 ', ' #B0C4DE ', ' #A6A6A6 ', ' #FF3E96 ', ' #FFB5C5 ', ' #FFEBCD ']) #数据源, display the value, display the label, Color Fig.set_size_inches (8,8)  #如果两个数字不相等会变成椭圆

　

5. Scatter chart

Fig,ax = Plt.subplots () ax.scatter (data[' tip '],data[' Total_bill ']) fig.set_size_inches (8,6) ax.set_xlabel (' Tip ', fontsize=18) Ax.set_ylabel (' Total consumption ', fontsize=18) plt.xticks (fontsize=12) plt.yticks (fontsize=12)

　　

6, several areas of the drawing method (one is using the above column chart that way Fig,ax = Plt.subplots), the other is the following, this can be customized to occupy the number of spaces)

Fig = plt.figure () Ax1 = Plt.subplot2grid ((2,3), (0,0)) Ax1.bar (data_bar.index,data_bar.values) fig.set_size_inches ( 12,6) Ax2 = Plt.subplot2grid ((2,3), (0,1), colspan=2) #占据几个空额, can also be rowspan, one is horizontal, one is vertical ax2.scatter (data[' Tip '],data[' Total_bill ']) ax3 = Plt.subplot2grid ((2,3), (1,0)) Ax3.barh (data_barh.index,data_barh.values)

7, two column chart comparison

Fig,ax = Plt.subplots () Ax.bar (Np.arange (4), data_bar.values,0.3)    #横坐标先用数字代替ax. Bar (Np.arange (4) +0.3,data_ bar.values*2,0.3)   #偏移一定量ax. Set_xticks (Np.arange (4) +0.15)   #重新设置x轴的位置ax. Set_xticklabels (Data_bar.index)   #重新设置名称

　　

Iv. Drawing (Seaborn)

　　

　

　　

　　

　　

Data Analysis--graphing (Python)