CODEWITHSUNDEEP
pythondataframelambda
Shane S
Shane S

Reputation: 2303

Pandas Apply Lambda causes TypeError: 'int' object is not subscriptable

I have this dataframe a sample of it is here:

Blockquote

I'm having trouble with this code. I'm getting the below error message: 

Traceback (most recent call last):   File "C:/Users/....py", line 12, in <module>
 dfF['CCRYear'] = dfF['Year'].apply(lambda x: 'True' if x['Year'] == x['MaxSS Year'] else 'False')   File "C:\Users\....py", line 3848, in apply
 mapped = lib.map_infer(values, f, convert=convert_dtype)   File "pandas\_libs\lib.pyx", line 2329, in pandas._libs.lib.map_infer   
 File "C:/Users/....py", line 12, in <lambda>
 dfF['CCRYear'] = dfF['Year'].apply(lambda x: 'True' if x['Year'] == x['MaxSS Year'] else 'False')
 TypeError: 'int' object is not subscriptable

The Columns 'Year' and 'MaxSS Year' are both int64 datatypes. So this is my code below:

import pandas as pd
import numpy as np

def cached_date_parser(s):
    if s in cache:
        return cache[s]
    dt = pd.to_datetime(s, format='%Y%m%d', coerce=True)
    cache[s] = dt
    return dt

dfF = pd.read_csv(r'C:\\Users\\....C_14.csv', parse_dates = [1], header='infer')
dfF['CCRYear'] = dfF['Year'].apply(lambda x: 'True' if x['Year'] == x['MaxSS Year'] else 'False')

Upvotes: 0

Views: 1010

Answers (1)

deadshot
deadshot

Reputation: 9061

The problem with your code is you are using apply() on a single columns and you are indexing that.

See what you doing just print the x in your lambda

df['Year'].apply(lambda x: print(x))

It will output below

2017
2018
2018
2015
2015
2015

Your code is trying to index the integer value x['Year']. In this x is integer years like 2018, 2019 etc.

Change this to 

dfF['CCRYear'] = dfF['Year'].apply(lambda x: 'True' if x['Year'] == x['MaxSS Year'] else 'False')

this

dfF['CCRYear'] = dfF['Year'] == dfF['MaxSS Year']

Using np.where()

dfF['CCRYear'] = np.where(dfF['Year'] == dfF['MaxSS Year'], 'True', 'False')

Upvotes: 1

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