使用matplotlib在一个子图中从 pandas DataFrame绘制两个直方图 [英] Plotting two histograms from a pandas DataFrame in one subplot using matplotlib

问题描述

我有一个如下所示的pandas数据框:

df = pd.DataFrame({ 'a_wood' : np.random.randn(100),
                 'a_grassland' : np.random.randn(100),
                 'a_settlement' : np.random.randn(100),
                 'b_wood' : np.random.randn(100),
                 'b_grassland' : np.random.randn(100),
                  'b_settlement' : np.random.randn(100)})

我想用一个子图中的每个数据帧头创建此数据的直方图.

fig, ax = plt.subplots(2, 3, sharex='col', sharey='row')

m=0
for i in range(2):
    for j in range(3):

        df.hist(column = df.columns[m], bins = 12, ax=ax[i,j], figsize=(20, 18))
        m+=1

为此，先前的代码可以完美运行，但现在我想将带眼的a和b标头(例如"a_woods"和"b-woods")组合到一个子图中，因此只有三个直方图.我尝试将两个列分配给df.columns[[m,m+3]]，但这不起作用.我也有一个索引列，其中包含"day_1"之类的字符串，我希望将其放在x轴上.有人可以帮我吗?

这就是我走了多远.

解决方案

我不知道我是否正确理解了您的问题，但是类似这样的事情可以将这些图结合起来.您可能想在Alpha上玩一些，然后更改标题.

#NOTE that you might want to specify your bins or they wont line up exactly
fig, ax = plt.subplots(1, 3, sharex='col', sharey='row', figsize=(20, 18))
n = 3
for j in range(n):
    df.hist(column=df.columns[j], bins=12, ax=ax[j], alpha=0.5, color='red')
    df.hist(column=df.columns[j+n], bins=12, ax=ax[j], alpha=0.5, color='blue')
    ax[j].set_title(df.columns[j][2:])

要将它们彼此相邻绘制，请尝试以下操作:

#This example doesnt have the issue with different binsizes within one subplot
fig, ax = plt.subplots(1, 3, sharex='col', sharey='row', figsize=(20, 18))

n = 3
colors = ['red', 'blue']

axes = ax.flatten()
for i,j in zip(range(n), axes):
    j.hist([df.iloc[:,i], df.iloc[:,i+n]], bins=12, color=colors)
    j.set_title(df.columns[i][2:])

I have a pandas dataframe like the following:

df = pd.DataFrame({ 'a_wood' : np.random.randn(100),
                 'a_grassland' : np.random.randn(100),
                 'a_settlement' : np.random.randn(100),
                 'b_wood' : np.random.randn(100),
                 'b_grassland' : np.random.randn(100),
                  'b_settlement' : np.random.randn(100)})

and I want to create histograms of this data with every dataframe header in one subplot.

fig, ax = plt.subplots(2, 3, sharex='col', sharey='row')

m=0
for i in range(2):
    for j in range(3):

        df.hist(column = df.columns[m], bins = 12, ax=ax[i,j], figsize=(20, 18))
        m+=1

For that the previous code works perfectly but now I want to combine eyery a and b header (e.g. "a_woods" and "b-woods") to one subplot so there would be just three histograms. I tried assigning two columns to df.columns[[m,m+3]] but this doesn't work. I also have an index column with strings like "day_1", which I want to be on the x-axis. Can someone help me?

This is how far i got.

解决方案

I don't know if I understood your question correctly, but something like this can combine the plots. You might want to play around a little with the alpha and change the headers.

#NOTE that you might want to specify your bins or they wont line up exactly
fig, ax = plt.subplots(1, 3, sharex='col', sharey='row', figsize=(20, 18))
n = 3
for j in range(n):
    df.hist(column=df.columns[j], bins=12, ax=ax[j], alpha=0.5, color='red')
    df.hist(column=df.columns[j+n], bins=12, ax=ax[j], alpha=0.5, color='blue')
    ax[j].set_title(df.columns[j][2:])

To plot them both next to eachother, try this:

#This example doesnt have the issue with different binsizes within one subplot
fig, ax = plt.subplots(1, 3, sharex='col', sharey='row', figsize=(20, 18))

n = 3
colors = ['red', 'blue']

axes = ax.flatten()
for i,j in zip(range(n), axes):
    j.hist([df.iloc[:,i], df.iloc[:,i+n]], bins=12, color=colors)
    j.set_title(df.columns[i][2:])

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