import numpy as np
import pandas as pd
def myDateParser(d):
#in format: 10/02/2018, out format: 181002
print("into myDateParser with ",d)
return(d[8:]+d[0:2]+d[3:5])
nd=myDateParser('10/02/2018')
print("nd=",nd)
rawDataFile="Transactions.CSV"
data = pd.read_csv(rawDataFile, header=1, usecols=[0,1,2,3,4,5,6,7],
parse_dates=True, date_parser=myDateParser)
print(data.head())
Gives a result without applying my date parser
into myDateParser with 10/02/2018
nd= 181002
Date Action ... Fees & Comm Amount
0 10/02/2018 Buy ... $3.95 -$281.24
1 10/02/2018 Sell to Open ... $5.60 $184.40
2 10/02/2018 Sell ... $3.99 $2799.59
3 10/02/2018 Buy to Close ... $5.60 -$735.60
4 10/02/2018 Buy ... $3.95 -$319.95
[5 rows x 8 columns]
Clearly I don't understand the instructions from the https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html page
I think you are looking for converters
pd.read_csv(r'File.csv', converters ={'Data':myDateParser})
Data
0 181002
1 181002
2 181002
3 181002
Also check date_parser here