In pandas, when removing data using str.split, how can I skip rows?
I have the following data:
Name X Y
AA:AA 0 0
AA:BB 1 1
AA:CC 2 2
GG:AB 3 3
GG:AC 4 4
How can I filter out 'AA' and the semicolon, but skip anything with GG?
I have used this to filter out the colon, and only keep the right side of the data, but for GG, I need to keep it as is
data['Name'] = data['Name'].str.split(":").str[1]
pandas numpy
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
add a comment |
I have the following data:
Name X Y
AA:AA 0 0
AA:BB 1 1
AA:CC 2 2
GG:AB 3 3
GG:AC 4 4
How can I filter out 'AA' and the semicolon, but skip anything with GG?
I have used this to filter out the colon, and only keep the right side of the data, but for GG, I need to keep it as is
data['Name'] = data['Name'].str.split(":").str[1]
pandas numpy
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
add a comment |
I have the following data:
Name X Y
AA:AA 0 0
AA:BB 1 1
AA:CC 2 2
GG:AB 3 3
GG:AC 4 4
How can I filter out 'AA' and the semicolon, but skip anything with GG?
I have used this to filter out the colon, and only keep the right side of the data, but for GG, I need to keep it as is
data['Name'] = data['Name'].str.split(":").str[1]
pandas numpy
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
I have the following data:
Name X Y
AA:AA 0 0
AA:BB 1 1
AA:CC 2 2
GG:AB 3 3
GG:AC 4 4
How can I filter out 'AA' and the semicolon, but skip anything with GG?
I have used this to filter out the colon, and only keep the right side of the data, but for GG, I need to keep it as is
data['Name'] = data['Name'].str.split(":").str[1]
pandas numpy
pandas numpy
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
asked Nov 16 '18 at 3:39
wegunterjrwegunterjr
768
768
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
Use str.contains and work on slice as:
mask = df['Name'].str.contains('GG')
df.loc[~mask,'Name'] = df.loc[~mask,'Name'].str.split(':').str[1]
print(df)
Name X Y
0 AA 0 0
1 BB 1 1
2 CC 2 2
3 GG:AB 3 3
4 GG:AC 4 4
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Use str.contains and work on slice as:
mask = df['Name'].str.contains('GG')
df.loc[~mask,'Name'] = df.loc[~mask,'Name'].str.split(':').str[1]
print(df)
Name X Y
0 AA 0 0
1 BB 1 1
2 CC 2 2
3 GG:AB 3 3
4 GG:AC 4 4
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
add a comment |
Use str.contains and work on slice as:
mask = df['Name'].str.contains('GG')
df.loc[~mask,'Name'] = df.loc[~mask,'Name'].str.split(':').str[1]
print(df)
Name X Y
0 AA 0 0
1 BB 1 1
2 CC 2 2
3 GG:AB 3 3
4 GG:AC 4 4
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
add a comment |
Use str.contains and work on slice as:
mask = df['Name'].str.contains('GG')
df.loc[~mask,'Name'] = df.loc[~mask,'Name'].str.split(':').str[1]
print(df)
Name X Y
0 AA 0 0
1 BB 1 1
2 CC 2 2
3 GG:AB 3 3
4 GG:AC 4 4
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
Use str.contains and work on slice as:
mask = df['Name'].str.contains('GG')
df.loc[~mask,'Name'] = df.loc[~mask,'Name'].str.split(':').str[1]
print(df)
Name X Y
0 AA 0 0
1 BB 1 1
2 CC 2 2
3 GG:AB 3 3
4 GG:AC 4 4
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
edited Nov 16 '18 at 4:41
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
answered Nov 16 '18 at 3:43
Sandeep KadapaSandeep Kadapa
7,388831
7,388831
add a comment |
add a comment |
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