Convert list of dictionaries to a pandas DataFrame

Question

I have a list of dictionaries like this:

[{\'points\': 50, \'time\': \'5:00\', \'year\': 2010}, 
{\'points\': 25, \'time\': \'6:00\', \'month\': \"february\"         


        

Answer 1

Pyhton3: Most of the solutions listed previously work. However, there are instances when row_number of the dataframe is not required and the each row (record) has to be written individually.

The following method is useful in that case.

import csv

my file= 'C:\Users\John\Desktop\export_dataframe.csv'

records_to_save = data2 #used as in the thread. 


colnames = list[records_to_save[0].keys()] 
# remember colnames is a list of all keys. All values are written corresponding
# to the keys and "None" is specified in case of missing value 

with open(myfile, 'w', newline="",encoding="utf-8") as f:
    writer = csv.writer(f)
    writer.writerow(colnames)
    for d in records_to_save:
        writer.writerow([d.get(r, "None") for r in colnames])