我有一个pandas数据帧,它是从具有以下结构的.csv文件中读取的:
Date, Latitude, Longitude, Brand, Pump, AKI, Trip Miles, Total Miles, Gallons, MPG, PPG, Total, Tires, MPG-D,
11/03/2013, 40° 1.729', -105° 15.516', Boulder Gas, 2, 87, 134.3, 134.3, 6.563, 20.46, 3.319, 21.78, Stock, ,
11/17/2013, 40° 1.729', -105° 15.516', Boulder Gas, 2, 87, 161.8, 296.0, 7.467, 21.67, 3.279, 24.48, Stock, ,
11/27/2013, 40° 0.872', -105° 12.775', Buffalo Gas, 6, 87, 180.8, 477.0, 8.096, 22.33, 3.359, 27.19, Stock, ,
12/07/2013, 40° 1.729', -105° 15.516', Boulder Gas, 6, 87, 265.1, 742.0, 12.073, 21.96, 3.179, 38.38, Stock, ,
12/11/2013, 40° 2.170', -105° 15.522', Circle K, 4, 87, 240.9, 983.0, 9.868, 24.41, 3.179, 31.37, Stock, ,
12/15/2013, 40° 8.995', -105° 7.876', Shell, 3, 87, 188.7, 1172, 8.596, 21.95, 3.059, 26.30, , ,
12/21/2013, 40° 1.770', -105° 15.481', Conoco, 3, 87, 113.8, 1286, 5.517, 20.62, 3.139, 17.32, Winter, ,
01/09/2014, 40° 1.729', -105° 15.516', Boulder Gas, 2, 87, 139.5, 1426, 7.181, 19.42, 3.279, 23.55, Winter, 21.3,
01/13/2013, 40° 1.770', -105° 15.481', Conoco, 7, 87, 260.8, 1688, 11.177, 23.33, 3.239, 36.20, Winter, 25.5,
01/18/2014, 40° 1.729', -105° 15.516', Boulder Gas, 2, 87, 102.0, 1790, 4.401, 23.18, 3.239, 14.26, Winter, 25.5,
02/02/2014, 39° 59.132', -105° 14.962', King Soopers, 5, 87, 175.3, 1965, 8.436, 20.78, 3.019, 25.47, Winter, 24.0,
02/03/2014, 40° 1.770', -105° 15.481', Conoco, 3, 87, 249.9, 2215, 10.452, 23.91, 3.219, 33.64, Winter, 25.2,
02/08/2014, 40° 2.170', -105° 15.522', Circle K, 7, 87, 186.4, 2402, 8.565, 21.76, 3.239, 27.74, Winter, 24.3,
02/13/2014, 40° 1.729', -105° 15.516', Boulder Gas, 8, 87, 79.6, 2481, 4.125, 19.30, 3.439, 14.19, Winter, 21.3,
03/06/2014, 40.014460, -105.225034, Conoco, 5, 87, 172.4, 2654, 8.618, 20.00, 3.779, 32.57, Winter, 21.9,
03/09/2014, 40.029498, -105.258117, Conoco, 6, 87, 230.4, 2884, 9.016, 25.55, 3.759, 33.89, Winter, 27.3,
03/17/2014, 40.036236, -105.258763, Conoco, 6, 87, 130.1, 3014, 5.368, 24.24, 3.719, 19.96, Winter, 25.8,
03/24/2014, 40.036236, -105.258763, Conoco, 1, 87, 282.3, 3297, 11.540, 24.46, 3.719, 42.92, Winter, 27.3,
我想绘制一个图,其中x轴是日期,左y轴是英里/加仑,右y轴是英里。在这个图中,我想用一种颜色显示“MPG”列的时间序列,用另一种颜色显示“MPG-D”的时间序列,用第三种颜色显示“Trip Miles”列的条形图。
我一直试图遵循http://pandas.pydata.org/pandas-docs/stable/visualization.html并使用下面的代码,但它生成了一个条形图和两个时间序列图,其中所有内容都在同一个轴上,而y标签没有显示。
%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv('mpg.csv', skipinitialspace=True,index_col='Date')
plt.figure()
ax = data['Trip Miles'].plot(kind='bar',secondary_y=['Trip Miles'])
ax.right_ax.set_ylabel('Miles')
ax.set_ylabel('Miles/Gallon')
data['MPG'].plot()
data['MPG-D'].plot()
您需要更明确地指定轴。试试这个:
编辑
所以这里的一个大问题是熊猫条形图和直线图的x轴格式有根本不同的方式。具体地说,条形图试图用记号和标签对每个条形图进行定性缩放。但在这里,你似乎对一个更像典型时间序列的格式感兴趣。
所以我建议你忘掉双轴图。相反,只需在两个完全分开的轴上绘图。像这样:
这给了我:
但是,如果真的需要条形图,或者真的希望所有东西都位于同一对x轴上,则必须使用matplotlib的API进行如下绘图:
这就给了我
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