如何从 dataframe 创建列表列表

Question

I have a dataframe df and I want to convert the dataframe to a list of list

    left_side                                  right_side                             similarity
0114600043776001 loan payment receipt         0421209017073500 loan payment receipt     0.689008
0114600043776001 loan payment receipt         0421209017073500 loan payment receipt     0.689008
vat onverve*issuance fee*506108               vat onverve*issuance fee*5061087       0.743522
vat onverve*issuance fee*506108               verve*issuance fee*506108*********1112    0.684342
verve*issuance fee*506108                     verve*issuance fee*506108*********8296    0.717817
verve*issuance fee*506108                     vat onverve*issuance fee*506108**         0.684342

maint fee recovery jun 2018                   vat maint fee recovery jun 2018          0.896607
maint fee recovery jun 2018                  vat maint fee recovery jun 2018         0.896607
maint fee recovery jun 2018                  vat maint fee recovery jun 2018         0.896607

Expected output should look like this:

[[0114600043776001 loan payment receipt, 0421209017073500 loan payment receipt,
  0421209017073500 loan payment receipt],
[vat onverve*issuance fee*506108, vat onverve*issuance fee*5061087, 
  verve*issuance fee*506108*********1112], 
[verve*issuance fee*506108*********8296, verve*issuance fee*506108                    
 vat onverve*issuance fee*506108** ],...]

I have tried grouping the above df by left_side column and converting the resulting df to a list, but the output is not what I expected. please I need your assistance on this

grouup_df = df.groupby(['left_side']).right_side.sum().to_frame()

grouup_df.values.tolist()

and the output looks like this:

['0421209017073500 loan payment receipt0421209017073500 loan payment receipt0421209017073500 loan payment receipt0421209017073500 loan payment receipt0421209017073500 loan payment receipt0421209017073500 loan payment receipt']
['vat maint fee recovery jun 2018vat maint fee recovery jun 2018vat maint fee recovery jun 2018maint fee recovery jul 2018maint fee recovery oct 2018maint fee recovery jul 2018maint fee recovery jul 2018']

Answer 1

import pandas as pd

dfold = {'left_side': ['string','string','string','string'],
            'right_side': ['string','string','string','string']
            }

df = pd.DataFrame(dfold, columns= ['left_side', 'right_side'])
print(df)
df_list = df.values.tolist()
print(df_list)

Answer 2

You can use df.groupby :

>>> [[k, *g] for k, g in df.groupby('left_side', sort=False)['right_side']]

[['0114600043776001 loan payment receipt',
  '0421209017073500 loan payment receipt',
  '0421209017073500 loan payment receipt'],
 ['vat onverve*issuance fee*506108',
  'vat onverve*issuance fee*5061087',
  'verve*issuance fee*506108*********1112'],
 ['verve*issuance fee*506108',
  'verve*issuance fee*506108*********8296',
  'vat onverve*issuance fee*506108**'],
 ['maint fee recovery jun 2018',
  'vat maint fee recovery jun 2018',
  'vat maint fee recovery jun 2018',
  'vat maint fee recovery jun 2018']]

Answer 3

I believe your looking for the to_records() method on a Datagrams. Try df.to_records() , you can find its documentation here