如何从数据帧创建列表列表

Question

我有一个数据帧df，我想把数据帧转换成一个列表

    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

预期输出应如下所示：

[[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** ],...]

我曾尝试通过left_side column对上述df进行分组，并将结果df转换为一个列表，但输出并不是我所期望的。我需要你的帮助

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

grouup_df.values.tolist()

输出如下所示：

['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

我相信您正在寻找数据报上的to_records()方法。 试试df.to_records()，你可以找到它的文档here

Answer 2

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 3

您可以使用^{}：

>>> [[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']]