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  • Python数据分析与机器学习-Matplot_1

    import pandas as pd
    unrate = pd.read_csv('unrate.csv')
    unrate['DATE'] = pd.to_datetime(unrate['DATE'])
    print(unrate.head(12))
    
             DATE  VALUE
    0  1948-01-01    3.4
    1  1948-02-01    3.8
    2  1948-03-01    4.0
    3  1948-04-01    3.9
    4  1948-05-01    3.5
    5  1948-06-01    3.6
    6  1948-07-01    3.6
    7  1948-08-01    3.9
    8  1948-09-01    3.8
    9  1948-10-01    3.7
    10 1948-11-01    3.8
    11 1948-12-01    4.0
    
    import matplotlib.pyplot as plt
    # matplotlib inline
    # Using the different pyplot functions, we can create, customize, and display a plot.
    plt.plot()
    plt.show()
    

    first_twelve = unrate[0:12]
    plt.plot(first_twelve['DATE'],first_twelve['VALUE'])
    plt.show()
    

    # While the y-axis looks fine, the x-axis tick labels are too close together and are unreadable
    # We can rotate the x-axis tick labels by 90 degrees so they don't overlap
    # We can specify degrees of rotation using a float or integer value.
    plt.plot(first_twelve['DATE'], first_twelve['VALUE'])
    plt.xticks(rotation=45)
    # print help(plt.xticks)
    plt.show()
    

    # xlabel(): accepts a string value, which gets set as the x-axis label.
    # ylabel(): accepts a string value, which is set as the y-axis label.
    # title(): accepts a string value, which is set as the plot title.
    
    plt.plot(first_twelve['DATE'], first_twelve['VALUE'])
    plt.xticks(rotation=90)
    plt.xlabel('Month')
    plt.ylabel('Unemployment Rate')
    plt.title('Monthly Unemployment Trends, 1948')
    plt.show()
    

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  • 原文地址:https://www.cnblogs.com/SweetZxl/p/11126782.html
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