删除列中具有nan值的行

代码示例

drop if nan in column

df = df[df['EPS'].notna()]

删除具有NaN值的行或列

df.dropna()     #drop all rows that have any NaN values
df.dropna(how='all')

使用nan panda拖放列

>>> df.dropna(axis='columns')
       name
0    Alfred
1    Batman
2  Catwoman

熊猫滴行与楠

import pandas as pd

df = pd.DataFrame({'values_1': ['700','ABC','500','XYZ','1200'],
                   'values_2': ['DDD','150','350','400','5000'] 
                   })

df = df.apply (pd.to_numeric, errors='coerce')
df = df.dropna()
df = df.reset_index(drop=True)

print (df)

从dataframe转换为list时删除nan值

a = [[y for y in x if pd.notna(y)] for x in df.values.tolist()]
print (a)
[['str', 'aad', 'asd'], ['ddd'], ['xyz', 'abc'], ['btc', 'trz', 'abd']]

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