Python 3.x 如何修复迭代过程中的ValueError?
由于值错误,无法迭代dataframe的分组值 <>我考虑的DF是,Python 3.x 如何修复迭代过程中的ValueError?,python-3.x,iteration,pandas-groupby,Python 3.x,Iteration,Pandas Groupby,由于值错误,无法迭代dataframe的分组值 我考虑的DF是, df: class section sub marks school city 0 I A Eng 80 jghss salem 1 I A Mat 90 jghss salem 2 I A Eng 50 jghss salem 3 III A Eng 80 gphss salem 4
df:
class section sub marks school city
0 I A Eng 80 jghss salem
1 I A Mat 90 jghss salem
2 I A Eng 50 jghss salem
3 III A Eng 80 gphss salem
4 III A Mat 45 gphss salem
5 III A Eng 40 gphss salem
6 III A Eng 20 gphss salem
7 III A Mat 55 gphss salem
为了将列(即“子”和“标记”)的值分组为列表,我使用
df_grp = df.groupby(['class','section','school','city']).agg(lambda x: list(x))
df_grp是
class section school city sub marks
I A jghss salem [Eng, Mat, Eng] [80, 90, 50]
III A gphss salem [Eng, Mat, Eng, Eng, Mat] [80, 45, 40, 20, 55]
现在我需要迭代df_grp,以便提取所有列的值,如
Row 1:-
class = I
section = A
school = jghss
city = salem
sub = [Eng, Mat, Eng]
marks = [80, 90, 50]
Row 2:-
class = III
section = A
school = gphss
city = salem
sub = [Eng, Mat, Eng, Eng, Mat]
marks = [80, 45, 40, 20, 55]
现在,为了迭代df_grp来提取列值,我使用了
for index,group in df_grp:
for subIndex, row in group.iterrows():
sub = row['sub']
marks = row['marks']
当我使用相同的方法时,它会返回
ValueError: too many values to unpack (expected 2)
下面是一个示例,它将返回第一列数据
groupby方法已返回一个数据帧,您无法再次循环它。我已尝试使用for index,group in data\u df\u grp.groupby(['class','section','school','city']):&for index,row in group.iterrows():您可以定义
data\u df\u grp
?请参阅“”@amannagariya,我也尝试过,它返回了ValueError
import pandas as pd
df1 = pd.DataFrame({
'atable': ['Users', 'Users', 'Domains', 'Domains', 'Locks'],
'column': ['col_1', 'col_2', 'col_a', 'col_b', 'col'],
'column_type':['varchar', 'varchar', 'int', 'varchar', 'varchar'],
'is_null': ['No', 'No', 'Yes', 'No', 'Yes'],
})
df1_grouped = df1.groupby('atable').agg(lambda x: list(x))
for row in df1_grouped.iterrows():
print(row[1].column)