![]() You will find the details of all the available parameters of the savefig() method in the official matplotlib documentation. There are many ways to use this method and customize the plot. You must use the savefig() method, which saves the current figure. However, we haven't yet discussed how to preserve the plots we create. We've discussed two attractive-looking plots so far. Plt.xticks(,city)įor summer_bar,winter_bar,ts,tw in zip(graph_summer,graph_winter,temp_summer,temp_winter): Graph_winter=plt.bar(x_pos_winter, temp_winter,color='dodgerblue',label='Winter',width=0.4) Graph_summer=plt.bar(x_pos_summer, temp_summer,color='tomato',label='Summer',width=0.4) Here's some sample code visualizing the temperatures of various cities in two seasons: temp_summer= You must carefully set the width and position of the bars on axes. You can group two bar plots by stacking one over the other. But it can be difficult for programmers new to Python to create these plots correctly. Additionally, bar plots are an excellent visualization tool for comparing the data of different groups. #2 Grouping Bar Plotsīar plots enable convenient comparison of data across categories. Also, note that the code above uses a random function. Running this code, you will notice that the same line looks different when presented in plots of different dimensions. Let's see the figure() class in action: import numpy as np You must pass these values as the figsize argument. It's as simple as passing the height and width of the plot in inches. You can use the matplotlib module's figure() class to change a plot's size. ![]() It's important for Python programmers to understand how to change the size of a plot because the plot size must be set according to the volume and complexity of the data. It might surprise you that this is the most searched question about matplotlib on Stackoverflow. However, you may have trouble understanding how it works without simple examples, especially if you're new to programming.īut you have nothing to worry about because, in this brief post, we discuss five tips for mastering matplotlib along with code samples. ![]() One of the best things about matplotlib is that it is quite beginner-friendly. ![]() It is a Python module that allows us to visualize data, helping us understand and analyze it to meet the business's goals. Whether you're learning Python just for fun or have a career as a data scientist or business analyst, it's a good idea to familiarize yourself with matplotlib. ![]()
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