[英]Convert string formatted as Pandas DataFrame into an actual DataFrame
我正在尝试将格式化的字符串转换为熊猫数据框。
[['CD_012','JM_022','PT_011','CD_012','JM_022','ST_049','MB_021','MB_021','CB_003'
,'FG_031','PC_004'],['NL_003','AM_006','MB_021'],
['JA_012','MB_021','MB_021','MB_021'],['JU_006'],
['FG_002','FG_002','CK_055','ST_049','NM_004','CD_012','OP_002','FG_002','FG_031',
'TG_005','SP_014'],['FG_002','FG_031'],['MD_010'],
['JA_012','MB_021','NL_003','MZ_020','MB_021'],['MB_021'],['PC_004'],
['MB_021','MB_021'],['AM_006','NM_004','TB_006','MB_021']]
我正在尝试使用pandas.DataFrame
方法来执行此操作,但结果是将整个字符串放置在DataFrame
一个元素内。
你是这个意思吗?
import pandas as pd
list_of_lists = [['CD_012','JM_022','PT_011','CD_012','JM_022','ST_049','MB_021','MB_021','CB_003'
,'FG_031','PC_004'],['NL_003','AM_006','MB_021'],
['JA_012','MB_021','MB_021','MB_021'],['JU_006'],
['FG_002','FG_002','CK_055','ST_049','NM_004','CD_012','OP_002','FG_002','FG_031',
'TG_005','SP_014'],['FG_002','FG_031'],['MD_010'],
['JA_012','MB_021','NL_003','MZ_020','MB_021'],['MB_021'],['PC_004'],
['MB_021','MB_021'],['AM_006','NM_004','TB_006','MB_021']]
result = pd.DataFrame({'result': list_of_lists})
最好的方法是用 '],[' 分隔符分割字符串,然后转换为 df。
import numpy as np
import pandas as pd
def stringToDF(s):
array = s.split('],[')
# Adjust the constructor parameters based on your string
df = pd.DataFrame(data=array,
#index=array[1:,0],
#columns=array[0,1:]
)
print(df)
return df
stringToDF(s)
祝你好运!
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