. 1 Import numpy AS NP 2 Import PANDAS AS PD . 3 Import matplotlib.pyplot AS PLT . 4 . 5 # import data . 6 DF = pd.read_excel ( " D: /test.xlsx " ) . 7 # Print (DF [:. 5]) . 8 . 9 # biaxial drawing of FIG. 10 # at the last histogram curve again add 11 # is a common x-axis, the left and right represent Y1, Y2 12 is 13 is 14 # scattergram painting 15 # determines two distribution pattern whether there is a correlation between the summary variables, or coordinate point 16 # polymerization scattergram data for comparison commonly boast class . 17 18 is 19 # Box-Plot line in FIG Box 20 is # is used as a display chart dispersion of a set of data information, 21 # feature is mainly used for the reaction raw data distribution may also be a plurality of sets of comparison data distribution 22 is 23 is # modify the background color graphic 24 IF 0: 25 AX = plt.gca () # GCA get current axis is obtained in the current coordinate system 26 is ax.patch.set_facecolor ( ' Gray ' ) 27 ax.patch.set_alpha (0.3 ) 28 PLT the .Show () 29 30 # correlation coefficient matrix of FIG, 31 is # PANDAS pd.scatter_matrix itself has a function of drawing () 32 # 33 is 34 is # Thermodynamic FIG 35 # Seaborn Python library is a streamlined, can create a chart meaningful, 36 # it is possible to use direct type DataFrame 37 [ # Import Seaborn AS SNS 38 is # sns.heatmap () 39 40 41 is # Data analysis structure 42 Pass
This section does not detail later can view the Seventh Python Data Analysis Division