Below is the output of my dataframe:
0 1
0 {"time": "2016-03-28T23:23:12Z" "target": "Raffi-Antilian"}
1 {"time": "2016-03-28T23:23:12Z" "target": "Caroline-Kaiser"}
How can I convert individual records from type dictionary to normal dataframe records with columns names being dictionary keys and record values being dictionary values? My desired output should be:
Time Target
0 2016-03-28T23:23:12Z Raffi-Antilian
1 2016-03-28T23:23:12Z Caroline-Kaiser
I have about 2000 records, Appreciate any help/guidance.
import json
data = []
with open('filename', 'r') as f:
for line in f:
data.append(json.loads(line))
pd.DataFrame(data)
gives
Out[49]:
target time
0 Raffi-Antilian 2016-03-28T23:23:12Z
1 Caroline-Kaiser 2016-03-28T23:23:12Z
You can read_csv with sep=';' if in file is not ;, so all data are in one Series. Then convert string to dictionary by ast.literal_eval and last use pd.DataFrame:
import pandas as pd
import ast
import io
temp=u"""{"time": "2016-03-28T23:23:12Z","target": "Raffi-Antilian"}
{"time": "2016-03-28T23:23:12Z","target": "Caroline-Kaiser"}"""
#after testing replace io.StringIO(temp) to filename
s = pd.read_csv(io.StringIO(temp), index_col=None, header=None, sep=';', squeeze=True)
print (s)
0 {"time": "2016-03-28T23:23:12Z","target": "Raf...
1 {"time": "2016-03-28T23:23:12Z","target": "Car...
Name: 0, dtype: object
L = s.apply(lambda x: ast.literal_eval(x)).tolist()
print (L)
[{'time': '2016-03-28T23:23:12Z', 'target': 'Raffi-Antilian'},
{'time': '2016-03-28T23:23:12Z', 'target': 'Caroline-Kaiser'}]
print (pd.DataFrame(L))
target time
0 Raffi-Antilian 2016-03-28T23:23:12Z
1 Caroline-Kaiser 2016-03-28T23:23:12Z
EDIT:
Another one line solution:
import pandas as pd
import json
print (pd.DataFrame([json.loads(line.strip()) for line in open('file.txt')]))
target time
0 Raffi-Antilian 2016-03-28T23:23:12Z
1 Caroline-Kaiser 2016-03-28T23:23:12Z
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