如何使用数据帧中的所有行名称标记轴 [英] how to label axis with all the row names from dataframe

问题描述

我的数据框包含大约430行:

I have the dataframe that contains about 430 rows:

     name         Right_Answers  Wrong_Answers
    Alice Ji      7                6
    Eleonora LI   2                5
    Mike The      6                5
    Helen Wo      5                3

为了可视化正确(红色)和错误(蓝色)答案的数量，我正在使用具有以下功能的matplotlib库:

for visualize the number of right (red) and wrong (blue) answers I'm using the matplotlib library with following functions:

g=df.plot(x='name', color=['b','r'], figsize=(100,50))  
ax.xaxis.set_major_locator(MultipleLocator(0.1))
labels = df.name.values[:]
ax = plt.gca()
ax.set_xticklabels(labels, rotation=90)

但是我在X轴上总是只有8个名称作为标签，而不是430(垂直旋转，因此有足够的空间容纳更多的行名称)！为什么会发生?我以为这种方法将所有行名放在轴labels = df.name.values[:]上，但显然没有. 您知道这个问题的其他解决方案吗? 我准备尝试使用seaborn或ggplot等其他库，即使我发现与matplotlib相比它们对dataframe来说都不是很舒服

but I have always only 8 names as labels on X axis, instead of 430 (rotated vertically, so there are enough of space for much more row names)! why it happens? I thought this method put all the row names on axis labels = df.name.values[:] but apparently not. do you know other solution for this problem? I'm ready to try another libraries as seaborn or ggplot, even if I haven't found them very comfortable for dataframe compared with matplotlib

推荐答案

假设数据在数据框中，则可以使用Pandas内置的绘图方法，例如:

Assuming your data is in a dataframe, you can use Pandas' built-in plotting methods, e.g.:

df.plot(kind='bar', color=['red', 'blue'])

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