删除列上有多个条件的行

Question

请对数据框使用以下代码。

删除“'Sachin'，'Virat']在'2014'年的总行数超过100的所有行

smd = [['Sachin', 1989, 130],
       ['Virat', 2014, 99],
       ['Sachin', 2014, 99],
       ['Virat', 2014, 183],
       ['Virat', 2014, 183],
       ['Rohit', 2014, 79],
       ['Virat', 2015, 129],
       ['Raina', 2014, 183],
       ['Rohit', 2014, 264],
       ['Sachin', 2014, 130],] 
df_smd = pd.DataFrame(smd, columns = ['Player', 'Year','Score'])
df_smd

Answer 1

您只需要写下您的条件：

1. 要获得平等，可以使用df.column_name == your_value
2. 要选择列表中的行，请isin进行操作。
3. 要反转条件，请使用~运算符。

一旦具备条件，则可以使用&运算符（而不是and）应用所有条件。

代码在这里：

smd = [['Sachin', 1989, 130],
       ['Virat', 2014, 99],
       ['Sachin', 2014, 99],
       ['Virat', 2014, 183],
       ['Virat', 2014, 183],
       ['Rohit', 2014, 79],
       ['Virat', 2015, 129],
       ['Raina', 2014, 183],
       ['Rohit', 2014, 264],
       ['Sachin', 2014, 130]]
df_smd = pd.DataFrame(smd, columns=['Player', 'Year', 'Score'])

# Select row where player is 'Sachin' or 'Virat'
condition_name = df_smd.Player.isin(['Sachin', 'Virat'])
condition_score = df_smd.Score > 100
condition_year = df_smd.Year == 2014

# Apply all the conditions
output = df_smd[~(condition_name & condition_score & condition_year)]
print(output)
#    Player  Year  Score
# 0  Sachin  1989    130
# 1   Virat  2014     99
# 2  Sachin  2014     99
# 5   Rohit  2014     79
# 6   Virat  2015    129
# 7   Raina  2014    183
# 8   Rohit  2014    264

您也可以使用drop来做到这一点（即使我发现它不太自然。）：

condition = (condition_name & condition_score & condition_year)
output = df_smd.drop(index=condition[condition].index)
print(output)
#    Player  Year  Score
# 0  Sachin  1989    130
# 1   Virat  2014     99
# 2  Sachin  2014     99
# 5   Rohit  2014     79
# 6   Virat  2015    129
# 7   Raina  2014    183
# 8   Rohit  2014    264