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iterate over row and get value from another column

Time:12-22

For example I have this dataframe :

X           Y
ABCDEFGH    220105
ABCDEFGH    22H1 4

and I want to do this

for name in df['X']:
    set1=name
    set2=the 6th char of Y
    set3=all numbers before 6th without space

so, I have tried

for name in df['X']:
    set1=name
    set2=df.loc[df['X']==name, 'Y'].str[5]
    set3=df.loc[df['X']==name, 'Y'].str[0:4]

Does not work because I have 2 same X values 'ABCDEFGH', so at set2 and set 3 the result is list. Meanwhile what I want is to have 2set1, 2set2, 2set 3 i.e

set1=ABCDEFGH
set2=5
set3=22010
set1=ABCDEFGH
set2=4
set3=22H1

CodePudding user response:

You can try:

for idx, row in df.iterrows():
    set1 = row['X']
    set2 = row['Y'][5]
    set3 = row['Y'].split()[0][:5]

Output if you had prints:

set1='ABCDEFGH'
set2='5'
set3='22010'
set1='ABCDEFGH'
set2='4'
set3='22H1'

CodePudding user response:

Use from this code

df.reset_index(drop=True, inplace=True)
for i in df.index:
    set1=df.at[i, 'X']
    set2=df.at[i, 'Y'][5]
    set3=df.at[i, 'Y'][0:4]

Output is

set1='ABCDEFGH'
set2='5'
set3='22010'
set1='ABCDEFGH'
set2='4'
set3='22H1'


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