CODEWITHSUNDEEP
pythonpandasdataframestackreshape
Jiamei
Jiamei

Reputation: 445

How to reshape data in Python

I have a dataframe that only contains one row, but multiple columns: enter image description here

I want to put every 5 columns to a new row. Here's the expected output: enter image description here

The original data was in a list, I converted to a dataframe. I don't know if it's easier to reshape through a list, but here's a sample list for you to try out, the original list is really long. ['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, ']

Upvotes: 0

Views: 215

Answers (4)

Rajith Thennakoon
Rajith Thennakoon

Reputation: 4130

You can do this easily using numpy

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)

Upvotes: 0

Yan Chih Ying
Yan Chih Ying

Reputation: 71

You can try using dictionary

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)

The output is enter image description here

Upvotes: 0

karthikeyan K
karthikeyan K

Reputation: 11

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()

Upvotes: 0

Mike67
Mike67

Reputation: 11342

It's easier to parse it as a list, then convert it to a dataframe.

  • For each entry, split the entry by ':' and add the key\value to a dictionary
  • Convert the dictionary to a dataframe

Try this:

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))

Output

                                                       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

Upvotes: 1

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