Error while trying to shift values in dataframe and get the difference

I made a user defined function to perform specific task on dataframe. It checks the condition on one column and uses the values of the second column to give the result in the third column.

Following is the function I wrote :

import numpy as np


def strk_inter(x):
   if x['SYMBOL'] == x['SYMBOL'].shift(1):
       a = x['STRIKE_PR'].shift(1) - x['STRIKE_PR']
   else :
       a = np.nan
    return a

optt_df['STRIKE_INTERVAL'] = optt_df.apply(strk_inter,axis=1)

It shows me an error of

> AttributeError: 'str' object has no attribute 'shift'

Dataset:

Expectation:

Pandas apply, with axis=1, is passing rows to your function, so x['SYMBOL'] is the value of the SYMBOL in that particular row, not the whole column that you can shift, hence the error message.

With the dataframe you provided:

import pandas as pd

df = pd.DataFrame({"SYMBOL": ["A", "A", "B", "B"], "STRIKE_PR": [1000, 1100, 950, 960]})

print(df)
# Output

  SYMBOL  STRIKE_PR
0      A       1000
1      A       1100
2      B        950
3      B        960

Here is one way to get the expected result:

def strk_inter(df_):
    for i in df_[df_["SYMBOL"] == df_.shift(-1)["SYMBOL"]].index:
        df_.at[i, "STRIKE_INTERVAL"] = (
            df_.at[i + 1, "STRIKE_PR"] - df_.at[i, "STRIKE_PR"]
        )
    return df_


print(strk_inter(df))
# Output

  SYMBOL  STRIKE_PR  STRIKE_INTERVAL
0      A       1000            100.0
1      A       1100              NaN
2      B        950             10.0
3      B        960              NaN