How do I combine columns (date, time, year) of a CSV file in the concat format (to create one new da-CodePudding

I am trying to combine three columns from a CSV file which happen to be 'day', 'month', and 'year'. I want to combine them into one 'date' column and then delete them. However, I keep receiving error messages. This is what I have so far:

import pandas as pd 
def airport_data(cur_file, airport_code):
    
    #import data 
    airportsearch = pd.read_csv('/work/Data.airports.csv')
    
    #drop all rows of data that do not belong to the desired airport code 
    airportsearch.dropna([lambda x:
        (x['origin_airport'].isin(['SFO'])) &
        (x)['destination_airport'].isin (['SFO'])]

    #make columns lower case
    airportsearch.columns = airportsearch.columns.str.lower()

    #create new column 
    df = pd.DataFrame(airportsearch, columns=["year", "month", "day"])
    df.dates = pd.to_datetime(df.Year) 

    #drop old columns 
    airportsearch.drop(columns=['day', 'month', 'year'], axis=1)

The error that I am getting reads: 'Dataframe' object has no attribute 'Year'. I am unsure what this even means. Any help would be appreciated! Here is the report of the error in case that helps

report of error message

CodePudding user response：

The error message you have linked is that "Year" is not a valid attribute of your DataFrame. Python is case-sensitive, and from your code, it seems you've called that column "year".

Also, please cut & paste error messages as text rather than using screenshots on StackOverflow