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使用seaborn为数据帧绘制直方图

[英]Plotting histogram using seaborn for a dataframe

I have a dataFrame which has multiple columns and many rows..Many row has no value for column so in the data frame its represented as NaN. 我有一个dataFrame,它有多列和多行。很多行没有列的值,所以在数据框中它表示为NaN。 The example dataFrame is as follows, 示例dataFrame如下,

df.head()
GEN Sample_1    Sample_2    Sample_3    Sample_4    Sample_5    Sample_6    Sample_7    Sample_8    Sample_9    Sample_10   Sample_11   Sample_12   Sample_13   Sample_14
A123    9.4697  3.19689 4.8946  8.54594 13.2568 4.93848 3.16809 NAN NAN NAN NAN NAN NAN NAN
A124    6.02592 4.0663  3.9218  2.66058 4.38232         NAN NAN NAN NAN NAN NAN NAN
A125    7.88999 2.51576 4.97483 5.8901  21.1346 5.06414 15.3094 2.68169 8.12449 NAN NAN NAN NAN NAN
A126    5.99825 10.2186 15.2986 7.53729 4.34196 8.75048 16.9358 5.52708 NAN NAN NAN NAN NAN NAN
A127    28.5014 4.86702 NAN NAN NAN NAN NAN NAN NAN NAN NAN NAN NAN NAN

I wanted to plot histogram for this dataFrame using seaborn function from python and so i was trying the following lines, 我想使用python的seaborn函数绘制这个dataFrame的直方图,所以我尝试了以下几行,

sns.set(color_codes=True)
sns.set(style="white", palette="muted")
sns.distplot(df)

But its throwing the following error, 但它抛出以下错误,

    ValueError                                Traceback (most recent call last)
    <ipython-input-80-896d7fe85ef3> in <module>()
          1 sns.set(color_codes=True)
          2 sns.set(style="white", palette="muted")
    ----> 3 sns.distplot(df)

    /anaconda3/lib/python3.4/site-packages/seaborn/distributions.py in distplot(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)
        210         hist_color = hist_kws.pop("color", color)
        211         ax.hist(a, bins, orientation=orientation,
    --> 212                 color=hist_color, **hist_kws)
        213         if hist_color != color:
        214             hist_kws["color"] = hist_color

   /anaconda3/lib/python3.4/site-packages/matplotlib/axes/_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
       5627             color = mcolors.colorConverter.to_rgba_array(color)
       5628             if len(color) != nx:
    -> 5629                 raise ValueError("color kwarg must have one color per dataset")
       5630 
       5631         # We need to do to 'weights' what was done to 'x'

    ValueError: color kwarg must have one color per dataset

Any helps/suggestions to get rid of this error would be greatly appreciated..!!! 任何帮助/建议摆脱这个错误将不胜感激.. !!!

Let's assume I have the excerpt from the data you have showed above (with only difference that on my machine NAN is NaN ). 让我们假设我从上面显示的数据中摘录(唯一的区别在于我的机器NANNaN )。

Then, the best graphical representation I can think of is grouped barplot: one group for every sample, within every group there are gene bars (some people call this histogram occasionally) 然后,我能想到的最佳图形表示是分组条形图:每个样本一组,每组内都有基因条(有些人偶尔称这个直方图)

In order to do that, you need first to "melt" your data, in R parlour, ie make it "long". 为了做到这一点,你需要首先在R客厅“融化”你的数据,即让它“长”。 Then, you can proceed with plotting. 然后,您可以继续绘图。

data = df.set_index('GEN').unstack().reset_index()
data.columns = ['sample','GEN', 'value']

sns.set(style="white")
g = sns.factorplot(x='sample'
                   ,y= 'value'
                   ,hue='GEN'
                   ,data=data
                   ,kind='bar'
                   ,aspect=2
                   )
g.set_xticklabels(rotation=30);

在此输入图像描述

Please, let us know if this is the type of plot you were after. 如果这是您所追求的情节类型,请告诉我们。

I had also thought the seaborn documentation mentioned that multiple columns could be plotted simultaneously, and highlighted by color by default. 我还认为seaborn文档提到可以同时绘制多个列,默认情况下用颜色突出显示。

But upon re-reading, I did not see anything. 但重新阅读后,我什么都没看到。 Instead, I think I inferred it from this tutorial , where part of the way through, the tutorial plots a data frame with multiple columns. 相反,我认为我从本教程推断出了这一点 ,其中部分内容通过,教程绘制了一个包含多列的数据框。


However, the "solution" is trivial, and hopefully exactly what you're looking for: 然而,“解决方案”是微不足道的,希望正是您正在寻找的:

sns.set(color_codes=True)
sns.set(style="white", palette="muted")
sns.distplot(df)

for col_id in df.columns:
    sns.distplot(df[col_id])

By default, this will alter the colors, "knowing" which one has already been used. 默认情况下,这将改变颜色,“知道”哪一个已被使用。

从上面的代码生成的图像(使用不同的数据集)

Note: I used a different data set, since I wasn't sure how to re-create yours. 注意:我使用了不同的数据集,因为我不确定如何重新创建你的数据集。

I had similar problem because my pandas.DataFrame had elements of type Object in a column I wanted to plot ( my_column ). 我有类似的问题,因为我的pandas.DataFrame在我想要绘制的列( my_column )中有Object类型的元素。 So that the command: 这样命令:

print(df[my_column])

gave me: 给我:

Length: 150, dtype: object

The solution was 解决方案是

sns.distplot(df[my_column].astype(float))

As the datatype of my_column transformed to: my_column的数据类型转换为:

Length: 150, dtype: float64

在此输入图像描述

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