从数据框熊猫中删除数据框

Question

我有toy_df

toy_df = pd.DataFrame(['animal':['cat','cat','cat','dog']

   animal
0     cat
1     cat
2     cat
3     dog

我正在使用toy_df_4 = toy_df[toy_df.animal == 'dog']

   animal
3     dog

我如何从通用toy_df_4删除某些daaframe toy_df

我尝试了toy df - toy_df_4，但此错误

TypeError: unsupported operand type(s) for -: 'str' and 'str'

此数据框是玩具，因此在实际数据集中，我具有许多条件的数据框

Answer 1

这里最简单的是用dog获取不匹配行的反转条件：

toy_df = pd.DataFrame({'animal':['cat','cat','cat','dog']})

toy_df_5 = toy_df[toy_df.animal != 'dog']
print (toy_df_5)
  animal
0    cat
1    cat
2    cat

但是如果确实需要按过滤后的DataFrame的索引值进行删除：

toy_df_4 = toy_df[toy_df.animal == 'dog']
toy_df_5 = toy_df.drop(toy_df_4.index)
print (toy_df_5)
  animal
0    cat
1    cat
2    cat

Answer 2

另一种方法是使用pandas.DataFrame.isin

toy_df = pd.DataFrame(['animal':['cat','cat','cat','dog']
toy_df_4 = toy_df[toy_df.animal == 'dog']
toy_df = toy_df[~toy_df.isin(toy_df_4)].dropna()

print(toy_df)
  animal
0    cat
1    cat
2    cat

Answer 3

toy_df = pd.DataFrame({'animal':['cat','cat','cat','dog']})
toy_df4 = toy_df[toy_df.animal=='dog']

df = toy_df.merge(toy_df_4, how='outer', indicator=True).loc[lambda x: x['_merge']=='left_only'].reset_index(drop=True)
df = df.drop('_merge', axis=1)

输出：

    animal
0    cat
1    cat
2    cat