如何在 Python 中重塑数据答案

【问题标题】：How to reshape data in Python如何在 Python 中重塑数据
【发布时间】：2020-12-23 07:03:07
【问题描述】：

我有一个只包含一行但多列的数据框：

我想将每 5 列放入一个新行。这是预期的输出：

原始数据在列表中，我转换为数据框。不知道通过一个列表来重塑是否更容易，但是这里有一个示例列表供您尝试，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, ']

【问题讨论】：

标签： python pandas dataframe stack reshape

【解决方案1】：

将其解析为列表更容易，然后将其转换为数据框。

对于每个条目，用 ':' 分割条目并将键\值添加到字典中
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

【讨论】：

【解决方案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

main()

【讨论】：

【解决方案3】：

你可以试试字典

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

【讨论】：

我非常喜欢您的回答，只需几个步骤即可完成。但是，您能解释一下 for 循环中的“_”是什么意思吗？
这只是一个传统的“一次性”变量名。看看这个link

【解决方案4】：

你可以使用 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)

【讨论】：