我有两个相同大小和尺寸的数据框import numpy as np
import pandas as pd
import scipy.stats as stats
import matplotlib.pyplot as plt
EI_levels = ["very low","low","medium","high","very high"]
#generate dataframe of values
EI = pd.DataFrame({'level': np.random.choice(EI_levels,p = [0.05, 0.05, 0.2, 0.4, 0.3],size=500)})
#generate contingency table of counts
EI_df = pd.DataFrame(EI.level.value_counts().reset_index())
EI_df.columns = ['level', 'count']
EI_df.set_index('level')
#Generate bar chart
ax = EI_df[['level', 'count']].plot(kind='bar', title ="Emotional Intelligence",figsize=(15, 10))
ax.xticks = (EI_df.level, ["very low","low","medium","high","very high"])
plt.show()
和df1。是否有一种简单的方法可以复制＆＃39; df1＆＃39;中的所有df2值到＆＃39; df2＆＃39; ？下面的示例演示了我想要的输出 NaN
.copynans()答案 0 :(得分：3)
无论
df1.where(df2.notnull())
或者
df1.mask(df2.isnull())
答案 1 :(得分：2)
#Use null cells from df1 as index to set the the corresponding cell to nan in df2
df2[df1.isnull()]=np.nan