Seaborn：设置distplot bin范围？

Question

所以我有这个数据集显示了数十亿国家的GDP（所以1万亿gdp = 1000）。

import numpy as np 
import pandas as pd 
import seaborn as sns 
import matplotlib.pyplot as plt 
%matplotlib inline 

df = pd.read_csv('2014_World_GDP') 
df.sort('GDP (BILLIONS)',ascending=False, inplace=True) 
sorted = df['GDP (BILLIONS)'] 

fig, ax = plt.subplots(figsize=(12, 8)) 
sns.distplot(sorted,bins=8,kde=False,ax=ax) 

上面的代码给我下图：

我想要做的不管是谁设置的垃圾箱范围，使他们看起来更像[250,500,750,1000,2000,5000,10000,20000什么]。

有没有办法做到这一点seaborn？

Answer 1

您可以使用对数箱，它可以很好地处理与您的数据一样的数据。这里有一个例子：

import numpy as np 
import pandas as pd 
import seaborn as sns 
import matplotlib.pyplot as plt 

df = pd.DataFrame() 
df['GDP (BILLIONS)'] = 2000*1./(np.random.random(250)) 
df.sort_values(by='GDP (BILLIONS)',ascending=False, inplace=True) 

fig, ax = plt.subplots(1,2,figsize=(8, 3)) 

sns.distplot(df['GDP (BILLIONS)'].values,bins=8,kde=False,ax=ax[0]) 
ax[0].set_title('Linear Bins') 

LogMin, LogMax = np.log10(df['GDP (BILLIONS)'].min()),np.log10(df['GDP (BILLIONS)'].max()) 
newBins = np.logspace(LogMin, LogMax,8) 
sns.distplot(df['GDP (BILLIONS)'].values,bins=newBins,kde=False,ax=ax[1]) 
ax[1].set_xscale('log') 
ax[1].set_title('Log Bins') 

fig.show()