如何重塑 Python 中的数据

Question

我有一个只包含一行但包含多列的数据框：

我想每 5 列换一行。这是预期的输出：

原始数据在列表中，我转换为数据框。我不知道通过列表重塑是否更容易，但这里有一个示例列表供您试用，原始列表真的很长。 ['review: I stayed around 11 days and enjoyed stay very much.', 'compound: 0.5106, ','neg: 0.0, ','neu: 0.708, ','pos: 0.292, ','review: Plans for weekend stay canceled due to Coronavirus shutdown.','compound: 0.0, ','neg: 0.0, ','neu: 1.0, ','pos: 0.0, ']

Answer 1

更容易将其解析为列表，然后将其转换为数据帧。

对于每个条目，用“:”拆分条目并将 key\value 添加到字典中
将字典转换为数据框

试试这个：

import pandas as pd

lst = ['review: I stayed around 11 days and enjoyed stay very much.', 'compound: 0.5106, ','neg: 0.0, ','neu: 0.708, ','pos: 0.292, ',
       'review: Plans for weekend stay canceled due to Coronavirus shutdown.','compound: 0.0, ','neg: 0.0, ','neu: 1.0, ','pos: 0.0, ']

dd = {}

for x in lst:
   sp = x.split(':')
   if sp[0] in dd:
      dd[sp[0]].append(sp[1].replace(',',"").strip())
   else:
      dd[sp[0]] = [sp[1].replace(',',"").strip()]
      
print(dd)
print(pd.DataFrame(dd).to_string(index=False))

输出

                                                       review compound  neg    neu    pos
          I stayed around 11 days and enjoyed stay very much.   0.5106  0.0  0.708  0.292
 Plans for weekend stay canceled due to Coronavirus shutdown.      0.0  0.0    1.0    0.0

Answer 2

def main():

data_new = ['review: I stayed around 11 days and enjoyed stay very much.', 'compound: 0.5106, ','neg: 0.0, ','neu: 0.708, ','pos: 0.292, ','review: Plans for weekend stay canceled due to Coronavirus shutdown.','compound: 0.0, ','neg: 0.0, ','neu: 1.0, ','pos: 0.0, ']

len_data = len(data_new)

proc_row_mul_of_five = len_data / 5

j = 5

k = 0 

for i in range(0,proc_row_mul_of_five):
    
    print(data_new[k:j])
    
    k = i + 5
    
    j = j + 5

主要（）

Answer 3

您可以尝试使用字典

lst = ['review: I stayed around 11 days and enjoyed stay very much.', 'compound: 0.5106, ','neg: 0.0, ','neu: 0.708, ','pos: 0.292, ',
       'review: Plans for weekend stay canceled due to Coronavirus shutdown.','compound: 0.0, ','neg: 0.0, ','neu: 1.0, ','pos: 0.0, ']

from collections import defaultdict
import pandas as pd

data_dict = defaultdict(list)
for _ in lst:
    header, value = _.split(':')
    data_dict [header].append(value.strip())

pd.DataFrame.from_dict(data_dict)

输出是

Answer 4

您可以使用 numpy 轻松做到这一点

import numpy as np
import pandas as pd
lis = np.array(['review: I stayed around 11 days and enjoyed stay very much.', 'compound: 0.5106, ','neg: 0.0, ','neu: 0.708, ','pos: 0.292, ','review: Plans for weekend stay canceled due to Coronavirus shutdown.','compound: 0.0, ','neg: 0.0, ','neu: 1.0, ','pos: 0.0, '])


columns = 5
t = np.char.split(lis,":")
cols,vals = list(zip(*t))
dff = pd.DataFrame(np.split(np.array(vals),len(vals)/columns),
                   columns=cols[:columns]).replace(",","",regex=True)

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