CODEWITHSUNDEEP
pythonpandasdate
Prima
Prima

Reputation: 70

How to count frequency last month in python?

i have a dataframe like this :

customer_id trx_date trx_amount last_trx
CS5295 2013-02-11 35 2014-11-25
CS5295 2014-11-25 54 2014-11-25
CS5295 2013-05-22 36 2014-11-25
CS5295 2012-12-24 36 2014-11-25
CS5295 2013-03-22 43 2014-11-25
CS5295 2013-02-11 25 2014-11-25

how can i count the trx_amount, from last month in last_trx, and customer_id as a parameter?

Expected Output :

customer_id trx_times
CS5295 1

from the last month of the date in last_trx, 2014-11-25

counting how many times did customer_id make a trx from 2014-10-25 to 2014-11-25

Upvotes: 2

Views: 500

Answers (1)

MathNerd572
MathNerd572

Reputation: 81

For simplicity I will call the DataFrame transact_df and assume it is a pandas dataframe. Additionally, the "last_trx" column is assumed be already be in the dataframe.

  1. Convert the columns to DateTime if not already done: Convert Pandas Column to DateTime

  2. Identify all rows that qualify: How would I compute exactly 30 days into the past with Python (down to the minute)?

valid_transacts_df = transact_df.loc[(transact_df['trans_date'] 
                                     > transact_df['last_trx'] - datetime.timedelta(30))]
  1. Count/sum the values you want:
# Number of transactions in the last 30 days
trx_times = len(valid_transacts_df)

# Sum of transactions in the last 30 days
total_amount = sum(valid_transacts_df['trx_amount'])

If necessary, you can combine steps 2 & 3 to shorten your code.

Upvotes: 2

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