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Today, the editor will share with you the relevant knowledge points about how Python+Matplotlib draws double y-axis images. The content is detailed and the logic is clear. I believe most people still know too much about this, so share this article for your reference. I hope you can get something after reading this article. Let's take a look at it.

Brief introduction of double Y-axis diagram

A double Y-axis diagram, as its name implies, means that there are two Y-axes in a single graph. This kind of graph is mainly used to show the relationship between two dependent variables and one independent variable, and the numerical units of the two dependent variables are still different. If we want to show the company's sales performance and cost changes in different months, we can show it with a double Y-axis chart. Depending on the variable, sales volume and cost have different units.

Realization idea

The idea of drawing double y-axis also uses the idea of matplotlib object-oriented drawing. Without specifying a location, create two coordinate systems on a canvas, the first of which is created normally and the second using the proprietary twinx () method.

Then the positions of the two coordinate systems coincide. The first coordinate system axis is on the left, and the coordinate system created by the twinx () method is on the right. Because there are two y-axes, when you operate on the y-axis properties, you need to be object-oriented, and if you simply use methods such as plt.ylabel (), you can only operate on the left axis, not the right axis.

The following is an example, the first is to guide the package and prepare the data, here prepare a set of sales data, and calculate its growth rate, reflect it on the right axis.

Implement code style one

The specific code is as follows:

Import matplotlib.pyplot as plt# generates a set of data x = range (7) y1 = [2000, 1600, 3000, 6200, 7000, 9800, 11000] y2 = [1] for i in range (len (y1)): if iTun1 = = len (y1): break rate = round (y1 [I + 1] / y1 [I]-1,2) y2.append (rate) fig = plt.figure (figsize= (10,8) Facecolor='#ff33ff') # font uses italic plt.rcParams ['font.sans-serif'] = [' STKAITI'] plt.rcParams ['axes.unicode_minus'] = False# background color is cc00ffplt.rcParams [' axes.facecolor'] ='# cc00ff'ax1 = fig.add_subplot (111) plt.title ('sales and its growth rate diagram', color='#ffff00', fontsize=25, yearly 1.04) plt.xticks (x, ['January', 'February', 'March') April, May, June, July], color='#ffff00', fontsize=15) plt.xlabel (month, color='#ff0033', fontsize=15) plt.yticks (color='#B22222', fontsize=15) ax1.bar (x, y1, color='#33ff66', label='left') ax1.set_ylabel ('sales (pieces)', color='#66ff00', fontsize=20) # add an axis ax2 = ax1.twinx () ax2.plot (x, y2) Color='#3399ff', linestyle='--', marker='o', linewidth=2) ax2.set_ylabel ("growth rate", color='#66ff00', fontsize=20) ax2.tick_params (axis='y', color='green', labelsize=15, labelcolor='#B22222') for a, b in zip (x, y2): plt.text (a, bau0.02,'% .2f'% b, ha='center', va='bottom', fontsize=15, color='red') plt.show ()

The effect of the image is as follows:

Style two

The specific implementation code is as follows

% matplotlib inlineimport matplotlib.pyplot as pltimport randomimport pandas as pdimport matplotlib as mplmpl.rcParams ['font.sans-serif'] = [' FangSong'] # specify the default font mpl.rcParams ['axes.unicode_minus'] = False # solve the problem that the saved image is a negative sign'-'displayed as a square # data preparation date= ["January", "February", "March", "April", "May", "June", "July" "August"] sales= [random.randint (10000Magneto 25000) for i in range (8)] cost= [int (iAccord 100)-random.randint (1Magazine 20) for i in sales] df=pd.DataFrame (data= {"sales volume": sales, "cost": cost}, index=date) # draw the first Y axis fig=plt.figure (figsize= (20d8), dpi=80) ax=fig.add_subplot (111) lin1=ax.plot (df.index,df ["sales volume"], marker= "o", label= "sales") ax.set_title ("double Y axis") Size=20) ax.set_xlabel ("time", size=18) ax.set_ylabel ("sales volume", size=18) for iMagle j in df ["sales volume"] .items (): ax.text (iGrain20 bottom str (j), va= "bottom", ha= "center", size=15) # draw another Y axis ax1=ax.twinx () lin2=ax1.plot (df.index,df ["cost"], marker= "o", color= "red") Label= "cost") ax1.set_ylabel ("cost (yuan)", size=18) # merge legend lins=lin1+lin2labs= [l.get _ label () for lin lins] ax.legend (lins,labs,loc= "upper left", fontsize=15) plt.show ()

The effect of the image is as follows:

These are all the contents of the article "how to draw double y-axis images by Python+Matplotlib". Thank you for reading! I believe you will gain a lot after reading this article. The editor will update different knowledge for you every day. If you want to learn more knowledge, please pay attention to the industry information channel.

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