下面是一个简单的函数，您可以通过传递dataframe和threshold直接使用它df
”’
pets location owner id
0 cat San_Diego Champ 123.0
1 dog NaN Ron NaN
2 cat NaN Brick NaN
3 monkey NaN Champ NaN
4 monkey NaN Veronica NaN
5 dog NaN John NaN
”’def rmissingvaluecol(dff,threshold):
l = []
l = list(dff.drop(dff.loc[:,list((100*(dff.isnull().sum()/len(dff.index))>=threshold))].columns, 1).columns.values)
print(“# Columns having more than %s percent missing values:”%threshold,(dff.shape[1] – len(l)))
print(“Columns:\n”,list(set(list((dff.columns.values))) – set(l)))
return l
rmissingvaluecol(df,1) #Here threshold is 1% which means we are going to drop columns having more than 1% of missing values
output
”’
Columns having more than 1 percent missing values
Original: https://blog.csdn.net/weixin_28723109/article/details/112964109
Author: 宋世泊
Title: python dataframe drop null值_删除Pandas数据框中的NaN/NULL列？
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