样本比例
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats
%matplotlib inline
_,axe = plt.subplots(1,2,figsize=(12,6))
train_data.label.value_counts().plot(kind='pie',autopct='%1.1f%%',shadow=True,explode=[0,0.1],ax=axe[0])
sns.countplot('label',data=train_data,ax=axe[1],)
概率分布
merchant_repeat_buy = [ rate for rate in train_data.groupby(['merchant_id'])['label'].mean() if rate <= 1 and rate > 0]
plt.figure(figsize=(8,4))
ax=plt.subplot(1,2,1)
sns.distplot(merchant_repeat_buy, fit=stats.norm)
ax=plt.subplot(1,2,2)
res = stats.probplot(merchant_repeat_buy, plot=plt)
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