How can I set the value for a specific row for a Pandas DataFrame in a for loop?

Question

for petid in X['PetID']:
    sentiment_file = datapath + '/train_sentiment/' + petid + '.json'
    if os.path.isfile(sentiment_file):
        json_data = json.loads(open(sentiment_file).read())
        X['DescriptionLanguage'] = json_data['language']
        X['DescriptionMagnitude'] = json_data['documentSentiment']['magnitude']
        X['DescriptionScore'] = json_data['documentSentiment']['score']
        # print(petid, sentiment_file,
        #       json_data['documentSentiment']['magnitude'])
    else:
        X['DescriptionLanguage'] = 'Unknown'
        X['DescriptionMagnitude'] = 0
        X['DescriptionScore'] = 0

This is what I have, but this doesn't work. It sets EVERY row to have those values for DescriptionLanguage , DescriptionMagnitude and DescriptionScore .

Answer 1

You can use .loc to set a individual value instead of a whole column. Here is a contained example

import pandas as pd
import numpy as np

X = pd.DataFrame(np.arange(5), columns=['PetID'])

for ind, row in X.iterrows():
    petid = row['PetID']
    X.loc[ind, 'DescriptionLanguage'] = 'No description for {}'.format(petid)

Answer 2

In addition to @Heikki Pulkkinen's excellent answer, you can also index the individual columns in the data frame, eg:

import pandas as pd
import numpy as np
data = np.array([np.arange(10)]*4).T
X = pd.DataFrame(data,columns=["PetID","DescriptionLanguage","DescriptionMagnitude","DescriptionScore"])
for i in range(len(X['PetID'])):
    X['DescriptionLanguage'][i] = 10*i

... which results in X becoming:

    PetID   DescriptionLanguage DescriptionMagnitude    DescriptionScore
0   0       0                   0                       0
1   1       10                  1                       1
2   2       20                  2                       2
3   3       30                  3                       3
4   4       40                  4                       4
5   5       50                  5                       5
6   6       60                  6                       6
7   7       70                  7                       7
8   8       80                  8                       8
9   9       90                  9                       9