堆叠Seaborn distplot时条形宽度会发生变化

Question

我正在尝试用Seaborn制作条形图，但是当我堆积图形时，条形宽度不均匀。我想使它们全部相同或更好，第一个比其他的更大（这是第一个的分解）。

以下是我的代码的模拟示例：

import pandas as pd
import seaborn as sns

Groups= pd.DataFrame([['E', 5L],['S0', 5L],['S', 4L],['S', 6L],['E', 4L],['S', 4L],
       ['E', 4L],['S', 4L],['S', 4L],['S0', 4L],['E', 5L],['S', 4L],['S', 4L],
       ['S', 4L],['E', 4L],['E', 5L],['E', 4L],['S0', 4L],['E', 4L],['S', 5L],
       ['E', 4L],['E', 4L],['S', 4L],['E', 4L],['S', 4L],['E', 4L],['E', 4L],
       ['S', 4L],['E', 4L],['E', 4L],['S0a', 6L],['E', 4L],['S0', 4L],['S0a', 4L],
       ['E', 5L],['E', 4L],['S0', 4L],['S', 6L],['S', 4L],['E', 4L],['E', 5L],
       ['E', 4L],['E', 4L],['E', 5L],['S', 5L]], columns=['MorphCen', 'NbGal'])


shift = 0.12
local_bins = (CompactGroups_raw['NbGal'].max()-CompactGroups_raw['NbGal'].min()+1)*10

ax1=sns.distplot(Groups['NbGal'], bins=local_bins, kde=False,rug=False, label="All")
ax1=sns.distplot(Groups['NbGal'].loc[Groups['MorphCen']=='S']+shift, 
                bins=local_bins, kde=False,rug=False,color='b', label="$S$ central")
ax1=sns.distplot(Groups['NbGal'].loc[Groups['MorphCen']=='E']+2*shift, 
                 bins=local_bins, kde=False,rug=False,color='r', label="$E$ central")
ax1=sns.distplot(Groups['NbGal'].loc[Groups['MorphCen']=='S0']+3*shift, 
                 bins=local_bins, kde=False,rug=False,color='g', label="$S_0$ central")
ax1=sns.distplot(Groups['NbGal'].loc[~Groups['MorphCen'].isin(['S','E','S0'])]+4*shift, 
                 bins=local_bins, kde=False,rug=False, color='y', label="Other central")

ax1.set(xlim=[Groups['NbGal'].min(), Groups['NbGal'].max()+1]);
ax1.set_ylabel('Object number')
loc1 = plticker.MultipleLocator(base=1.0) 
ax1.xaxis.set_major_locator(loc1)
ax1.legend();

我得到的是这个数字：

如何管理宽度？我认为它是由垃圾箱自动设置的，但是所有垃圾箱都相同并不能解决问题。

Answer 1

好的，多亏了mwaskom，它确实有效。这是正确的代码：

min_NbGals = CompactGroups_raw['NbGal'].min()
max_NbGals = CompactGroups_raw['NbGal'].max()

local_bins = (max_NbGals-min_NbGals+1)*10
ax1=sns.distplot(CompactGroups_raw['NbGal'], bins=local_bins, hist_kws={"range": [min_NbGals,max_NbGals]}, kde=False,rug=False, color='k', label="All")
ax1=sns.distplot(CompactGroups_raw['NbGal'].loc[CompactGroups_raw['MorphCen']=='S']+shift, 
                bins=local_bins, hist_kws={"range": [min_NbGals,max_NbGals]}, kde=False,rug=False,color='b', label="$S$ central")
ax1=sns.distplot(CompactGroups_raw['NbGal'].loc[CompactGroups_raw['MorphCen']=='E']+2*shift, 
                 bins=local_bins, hist_kws={"range": [min_NbGals,max_NbGals]}, kde=False,rug=False,color='r', label="$E$ central")
ax1=sns.distplot(CompactGroups_raw['NbGal'].loc[CompactGroups_raw['MorphCen']=='S0']+3*shift, 
                 bins=local_bins, hist_kws={"range": [min_NbGals,max_NbGals]}, kde=False,rug=False,color='g', label="$S_0$ central")
ax1=sns.distplot(CompactGroups_raw['NbGal'].loc[~CompactGroups_raw['MorphCen'].isin(['S','E','S0'])]+4*shift, 
                 bins=local_bins, hist_kws={"range": [min_NbGals,max_NbGals]}, kde=False,rug=False, color='y', label="Other central")
ax1.set(xlim=[CompactGroups_raw['NbGal'].min(), CompactGroups_raw['NbGal'].max()+1]);
ax1.legend();