Create an excel file using pandas in python:

users = [{
     'user_id': 1
 }, {
     'user_id': 2
 }]
 df = pandas.DataFrame(users, columns=['user_id'])
 filename = 'users_info_%s.xlsx' % random.randint(0, 100)
 writer = pandas.ExcelWriter(filename, engine='xlsxwriter')
 df.to_excel(writer, sheet_name='user information')

#pandas #python #excel #dataframe

Data Analysis


Create a dataframe from dictionary in Pandas:

import pandas
 data = [{'id': 1, 'name': 'alireza'}, {'id': 2, 'name': 'Mohsen'}]
 # Creating a dataframe from a dictionary object
 df = pandas.DataFrame(data)

Now if you print dataframe:

> df
    id     name
 0   1  alireza
 1   2   Mohsen

NOTE: the first column is the index column.


In order to turn it to a dictionary after your aggregation, analysis, etc just use to_dict like below:

df.to_dict(orient='records')
 [{'id': 1, 'name': 'alireza'}, {'id': 2, 'name': 'Mohsen'}]

You are right! We didn't do anything useful on records, but the goal is to tell you how to turn dataframe to a dictionary not more.

NOTE: on older version of pandas you have to use outtype='records' rather than orient='records'.

#python #pandas #to_dict #outtype #orient #dictionary #dataframe

How to sort data based on a column in Pandas?

You can use sort_values in order to sort data in a dataframe:

df.sort_values(['credit'], ascending=False, inplace=True)

The above sample assumes that you have a data frame called df and sort it based on user credit. The sort order is Descending (ascending=False). and it sorts in place (You don't have to copy the result into a new dataframe).

#python #pandas #dataframe #sort #inplace