Shulou(Shulou.com)06/01 Report--

This article mainly introduces "how to use Python to make a column chart". In daily operation, I believe many people have doubts about how to use Python to make a column chart. The editor consulted all kinds of data and sorted out a simple and easy-to-use method of operation. I hope it will be helpful for you to answer the doubt of "how to use Python to make a column chart". Next, please follow the editor to study!

1 Vertical column chart (ordinary column chart)

The python code for drawing a normal bar chart is as follows:

(swipe left and right to see all the code)

"- *-coding:utf-8-* -" declares that the encoding format is utf-8 3 4import matplotlib as mpl 5import matplotlib.pyplot as plt 6 7mpl.rcParams ["font.sans-serif"] = ["SimHei"] "specifies the font as SimHei, which is used to display Chinese. If Ariel, Chinese will be garbled 9mpl.rcParams ["axes.unicode_minus"] = False10# used to display the minus sign 11121314x = [1ping2jing3jingle 45jingle 6pjing8] 15y = [30pyrll 42pyrus 53pyrus 81pyrus 25] # data abels= ["A", "B", "C", "D", "E", "F", "G", "H"] # defines the label plt.bar of the column (XJI YJI rgb = "center", color= "rgb", tick_label=labels,hatch= ") Ec='gray') # draw a vertical bar chart, and hatch defines the twill filling of the column chart Omitting this parameter means that it is not populated by default. The # bar bar chart function also has the following parameters: # color: color, you can take a specific color such as red (abbreviated to r), or you can use rgb to make each column use a different color. # Stroke: edgecolor (ec): edge color; linestyle (ls): edge style; linewidth (lw): edge thickness # fill: hatch, value: /, |, -, +, x _

2 horizontal bar chart

Adjust the above code a few lines to draw a horizontal bar chart.

(1) Line 19 "plt.bar" plus the letter h, that is, "plt.barh"

(2) swap the x and y in "plt.xlabel" and "plt.ylable" in lines 28 and 29.

The drawing results are as follows:

3 stacked bar chart

Adjust lines 14-21 of the code in point 1 as follows:

(swipe left and right to see all the code)

X = [1 labels=, "B", "C", "D", "E", "F", "G", "H"] # defines the label of the column plt.bar (XJI YJ alignn = "center", color= "b", tick_label=labels,hatch= ", ec='gray') # draws a vertical bar chart, and hatch defines the twill filling of the column chart. Plt.bar (xmemy y1 recording = "center", color= "g", tick_label=labels,hatch= "", ec='gray',bottom=y)

The effect of drawing a vertical stack diagram is as follows:

Line 22 above is to draw the second group of Y1 histograms. Different from the plt.bar () function drawn by the first group of y histograms, there is an additional bottom=y in the drawing parameters of the Y1 histogram, that is, the bottom of the column chart is set to the first set of y values, so that Y1 can be stacked on y. The python code for the horizontal stacked bar chart is similar to the above.

4 juxtaposed bar chart

Juxtaposed histograms, especially those with error bars, are our most commonly used histograms.

The complete code is as follows:

(swipe left and right to see all the code)

#-*-coding:utf-8-*-# declare the encoding format as utf-8import matplotlib as mplimport matplotlib.pyplot as pltimport numpy as npmpl.rcParams ["font.sans-serif"] = ["SimHei"] # specify the font as SimHei to display Chinese, if Ariel, the Chinese will garbled mpl.rcParams ["axes.unicode_minus"] = False# to normally display the negative sign x = np.arange (8) # generate a sequence of 1x8 # Note: the numpy library is used here At the beginning of the program, you need to guide the package "import numpy as np" y = [10pint 11Power22] std_err= [2pje 4je 5e 68pl 62pl 75] # error stick y1 = [15pint 23pas 4pens 4pens 4pens 87pens 899pals 85] std_err1= [1pens 2pens 1pens 2pens 2pr 2] # error bar # data error_attri = dict (elinewidth=1,ecolor= "r", capsize=3) # defines the dictionary data of the error bar attributes. These three parameters define the linewidth, color and hat size of the error rod tick_label= ["A", "B", "C", "D", "E", "F", "G", "H"] # define the label bar_width=0.35# of the column, define the column width plt.bar (XMagany barometric width = "lightgreen", align= "center", label= "before doping", yerr=std_err,error_kw=error_attri) # draw a vertical bar chart Hatch defines the twill filling of a histogram Omitting this parameter means that it is not populated by default. 32plt.xticks (xylene bargaining widthmark 2) 3334plt.xlabel ("sample number") 35plt.ylabel ("degradation rate /%") 36plt.legend () 37plt.show ()

5 stacking error bar column diagram

In the previous point 4, modify lines 28-32 as follows:

28plt.bar (XJ y center = "g", align= "center", label= "before doping", yerr=std_err,error_kw=error_attri) 29# draws a vertical histogram, and hatch defines the twill filling of the histogram, omitting this parameter means that it is not filled by default. 30plt.bar (xmemy1 yerr=std_err1,error_kw=error_attri bottomized label = "y", align= "center", label= "after doping", yerr=std_err1,error_kw=error_attri) color = "y"

The stacking error histogram can be drawn, and the effect is as follows:

At this point, the study on "how to use Python to make a bar chart" is over. I hope to be able to solve your doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.