Bdtyktl

name,age

something

tom,20

df = pd.read_csv('file', header=None)



     0           1

1    name        age

2    something   NaN

3    tom         20

# in pseudocode

df['_count_separators'] = len(df.raw_value.count(','))



     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

name,age

something

tom,20

df = pd.read_csv('file', header=None)



     0           1

1    name        age

2    something   NaN

3    tom         20

# in pseudocode

df['_count_separators'] = len(df.raw_value.count(','))



     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

name,age

something

tom,20

df = pd.read_csv('file', header=None)



     0           1

1    name        age

2    something   NaN

3    tom         20

# in pseudocode

df['_count_separators'] = len(df.raw_value.count(','))



     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

name,age

something

tom,20

df = pd.read_csv('file', header=None)



     0           1

1    name        age

2    something   NaN

3    tom         20

# in pseudocode

df['_count_separators'] = len(df.raw_value.count(','))



     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

add a comment | 

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active

oldest

votes

df = pd.read_csv('file', header=None)

df2 = pd.read_csv('file', header=None,sep='|') # using another sep for read your csv again 



df2['0'].str.findall(',').str.len() # then one row into one cell , using str find 

0    1

1    0

2    1

3    5

Name: 0, dtype: int64



df['_count_separators']=df2['0'].str.findall(',').str.len()

name,age

something

tom,20

something,,,,,somethingelse

df = pd.read_csv('file', header=None)

df2 = pd.read_csv('file', header=None,sep='|') # using another sep for read your csv again 



df2['0'].str.findall(',').str.len() # then one row into one cell , using str find 

0    1

1    0

2    1

3    5

Name: 0, dtype: int64



df['_count_separators']=df2['0'].str.findall(',').str.len()

name,age

something

tom,20

something,,,,,somethingelse

df = pd.read_csv('file', header=None)

df2 = pd.read_csv('file', header=None,sep='|') # using another sep for read your csv again 



df2['0'].str.findall(',').str.len() # then one row into one cell , using str find 

0    1

1    0

2    1

3    5

Name: 0, dtype: int64



df['_count_separators']=df2['0'].str.findall(',').str.len()

name,age

something

tom,20

something,,,,,somethingelse

df = pd.read_csv('file', header=None)

df2 = pd.read_csv('file', header=None,sep='|') # using another sep for read your csv again 



df2['0'].str.findall(',').str.len() # then one row into one cell , using str find 

0    1

1    0

2    1

3    5

Name: 0, dtype: int64



df['_count_separators']=df2['0'].str.findall(',').str.len()

name,age

something

tom,20

something,,,,,somethingelse

add a comment | 

# s = pd.read_csv(pd.compat.StringIO(text), sep=r'|', squeeze=True, header=None)

s = pd.read_csv('/path/to/file.csv', sep=r'|', squeeze=True, header=None)

df = pd.concat([

       s.str.split(',', expand=True), 

       s.str.count(',').rename('_count_sep')

    ], axis=1)



df

           0     1  _count_sep

0       name   age           1

1  something  None           0

2        tom    20           1

# s = pd.read_csv(pd.compat.StringIO(text), sep=r'|', squeeze=True, header=None)

s = pd.read_csv('/path/to/file.csv', sep=r'|', squeeze=True, header=None)

df = pd.concat([

       s.str.split(',', expand=True), 

       s.str.count(',').rename('_count_sep')

    ], axis=1)



df

           0     1  _count_sep

0       name   age           1

1  something  None           0

2        tom    20           1

# s = pd.read_csv(pd.compat.StringIO(text), sep=r'|', squeeze=True, header=None)

s = pd.read_csv('/path/to/file.csv', sep=r'|', squeeze=True, header=None)

df = pd.concat([

       s.str.split(',', expand=True), 

       s.str.count(',').rename('_count_sep')

    ], axis=1)



df

           0     1  _count_sep

0       name   age           1

1  something  None           0

2        tom    20           1

# s = pd.read_csv(pd.compat.StringIO(text), sep=r'|', squeeze=True, header=None)

s = pd.read_csv('/path/to/file.csv', sep=r'|', squeeze=True, header=None)

df = pd.concat([

       s.str.split(',', expand=True), 

       s.str.count(',').rename('_count_sep')

    ], axis=1)



df

           0     1  _count_sep

0       name   age           1

1  something  None           0

2        tom    20           1

add a comment | 

df = pd.read_csv('file', header=None)

df['_count_separators'] = df.count(axis='columns')

print(df)

output: 

     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

df = pd.read_csv('file', header=None)

df['_count_separators'] = df.count(axis='columns')

print(df)

output: 

     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

df = pd.read_csv('file', header=None)

df['_count_separators'] = df.count(axis='columns')

print(df)

output: 

     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

df = pd.read_csv('file', header=None)

df['_count_separators'] = df.count(axis='columns')

print(df)

output: 

     0           1      _count_separators

1    name        age   1

2    something   NaN   0

3    tom         20    1

add a comment | 

add a comment |