CODEWITHSUNDEEP
pythonpandasnumpy
gerscorpion
gerscorpion

Reputation: 188

Pandas dataframe grouped operation inside numpy function

I have a data frame consisting of thousands of stock quotes, ordered by symbol(tic) and Date.

    Date    tic    prccd
0   1-1-20  AAPL    4.00
1   2-1-20  AAPL    4.10
2   3-1-20  AAPL    4.12
3   1-1-20  MSFT    6.00
4   2-1-20  MSFT    6.15
5   3-1-20  MSFT    6.10

With

stocks_data['log_return'] = np.log(1 + stocks_data.groupby('tic')['prccd'].pct_change())

I aim to get the logarithmic daily return of these stocks. Does the numpy function acknowledge the groupby tic operation?

Upvotes: 0

Views: 40

Answers (1)

ipj
ipj

Reputation: 3598

To calculate daily log returns per tic group use:

stocks_data['log_return'] = df.groupby('tic').prccd.transform(lambda x: np.log(x) - np.log(x.shift(1)))

or equivalent formula:

stocks_data['log_return'] = df.groupby('tic').prccd.transform(lambda x: np.log(x / x.shift(1)))

result:

     Date   tic  prccd  log_return
0  1-1-20  AAPL   4.00         NaN
1  2-1-20  AAPL   4.10    0.024693
2  3-1-20  AAPL   4.12    0.004866
3  1-1-20  MSFT   6.00         NaN
4  2-1-20  MSFT   6.15    0.024693
5  3-1-20  MSFT   6.10   -0.008163

Upvotes: 2

Related Questions