如何调用熊猫str.split（）而不是python内置的str.split（）

Question

I am trying to locate all the rows of a dataframe whose one attribute (say id_proof) value matches to the second part of another column (say adr_proof) that starts with a fixed word (say PARENT) and also the corresponding values should match which are part of the same dataframe.

For example, in the dataframe :

import pandas as pd

main = {'account_number' : [1,2,3,4,5,6,7,8,9,10,11,12],
    'id_proof' : ['A','B','B','A','C','C','X','Y','X','Y','Y','X'],
    'id_value' : [101,201,301,401,501,601,111,222,333,444,555,666],
    'adr_proof' : ['Z','E','E','G','G','I','PARENT A','PARENT B','PARENT   B','PARENT C','PARENT C','PARENT A'],
    'adr_value' : [11,22,33,44,55,66,101,201,301,501,601,401]}
main = pd.DataFrame(main)

I am trying to achieve :

node1    node2    relation
  1        7      parent-child
  2        8      parent-child
  3        9      parent-child
  4       12      parent-child
  5       10      parent-child
  6       11      parent-child

Below is my code. I am aware that my code is incomplete. I am stuck with the split() function. I am new to python and pandas and am not sure how to invoke pandas' split() function rather than python's built-in str.split() function. I have gone through this question

import pandas as pd

main = {'account_number' : [1,2,3,4,5,6,7,8,9,10,11,12],
    'id_proof' : ['A','B','B','A','C','C','X','Y','X','Y','Y','X'],
    'id_value' : [101,201,301,401,501,601,111,222,333,444,555,666],
    'adr_proof' : ['Z','E','E','G','G','I','PARENT A','PARENT B','PARENT B','PARENT C','PARENT C','PARENT A'],
    'adr_value' : [11,22,33,44,55,66,101,201,301,501,601,401]}
main = pd.DataFrame(main)

df_group_count = pd.DataFrame({'count' : main.groupby(['adr_proof']).size()}).reset_index()
adr_type = df_group_count['adr_proof']
adr_type_parent = adr_type.loc[adr_type.str.startswith('PARENT',na=False)]

df_j_ = pd.DataFrame()
for j in adr_type_parent:
    dfn_j = main.loc[(main['adr_proof'] == j)]
    adr_type_parent_type = j.split(' ',expand=True,n=1)
    res = main.loc[(main['id_proof'] == adr_type_parent_type[1]) & (main['id_value'] == dfn_j['adr_value'])]

res

Please provide a way to achieve my goal. The output is another dataframe. Please excuse for bad code or any violations. A completely different approach is also appreciated. Thank You.

Answer 1

You can't invoke str.split() of the pandas library in your particular case because you are using the DataFrame object, and this particular object does not implement str.split() . Only the Series object implements str.split() .

Answer 2

Since your main question seems to be how to incorporate pandas split function:

You can isolate the rows containing the keyword 'PARENT' using this:

parent_main = main[main.adr_proof.str.split(' ').str[0] == 'PARENT']

Now, you can easily extract the second value:

parent_main.adr_proof.str.split(' ').str[-1]

Answer 3

After investigating this and also discussing about this in the #python channel on IRC network freenode.net, I have an answer for you. You can't overshadow str.split() of Python with the str.split() of the pandas library.

Also, the DataFrame object has no str.split() . I have read the whole API and also played with from ... import ... to somehow import str.split() from pandas and overshadow the str.split() of Python.

The DataFrame object you are using in your code has no str.split() . The only reason str.split() in your code doesn't throw an error is because it just so happens Python has str.split() built in and uses that.

The only pandas object I could find that has str.split() is the Series object, pandas.Series.str.split() . But you're not using the Series object, you are using the DataFrame object. I'm sorry, there's nothing to be done.

If you ask me, the structure of pandas is broken. You can't just import str.split() , because str is basically a StringMethods object and this object lives under the strings package, which lives in the core package, which lives in the pandas top-level package. It's a mess! I wasted 2 hours of my life to understand its package/module/object structure.

Also, pandas.Series.str.split() is basically pandas.core.series.Series.str.split() . I just gave up!

Try to import str.split() from pandas and you'll get a Nobel prize!