Why is groupby and rolling not working together?

Question

I have a df that I scraped from coinmarketcap. I am trying to calculate volitlity metrics for the close_price column but when I use a groupby I'm getting an error message:

final_coin_data['vol'] = final_coin_data.groupby('coin_name')['close_price'].rolling(window=30).std()
TypeError: incompatible index of inserted column with frame index

df structure (the 'Unnamed:0' came after I loaded my CSV):

    Unnamed: 0  close_price coin_name   date            high_price  low_price    market_cap         open_price  volume
0   1           9578.63     Bitcoin     Mar 11, 2018    9711.89     8607.12      149,716,000,000    8852.78     6,296,370,000
1   2           8866.00     Bitcoin     Mar 10, 2018    9531.32     8828.47      158,119,000,000    9350.59     5,386,320,000
2   3           9337.55     Bitcoin     Mar 09, 2018    9466.35     8513.03      159,185,000,000    9414.69     8,704,190,000
3   1           9578.63     Monero      Mar 11, 2018    9711.89     8607.12      149,716,000,000    8852.78     6,296,370,000
4   2           8866.00     Monero      Mar 10, 2018    9531.32     8828.47      158,119,000,000    9350.59     5,386,320,000
5   3           9337.55     Monero      Mar 09, 2018    9466.35     8513.03      159,185,000,000    9414.69     8,704,190,000

(ignore the incorrect prices, this is the basics of the df)

When using the following code:

final_coin_data1['vol'] = final_coin_data.groupby('coin_name')['close_price'].rolling(window=30).std().reset_index(0,drop=True)

I got a MemoryError. I thought I was using groupby correctly. If I take out the final_coin_data1['vol'] = then I get a series which appears correct, but it won't let me insert back into the df.

When I first started this project. I had just 1 coin and used the code below and it calculated volatility no problem.

 final_coin_data1['vol'] = final_coin_data['close_price'].rolling(window=30).std()

Answer 1

When I ran this,

final_coin_data['close_price'].rolling(window=30).std()

an index column and result column are generated. When I tried to merge back to the original df as a new column final_coin_data1['vol'] I was getting an error TypeError: incompatible index of inserted column with frame index so to correct this, I reset_index(drop=True) then this eliminated the index which allowed the result to be joined on the final_coin_data1['vol'].

The final functioning code looks like this:

final_coin_data1['vol'] = final_coin_data.groupby('coin_name')['close_price'].rolling(window=30).std().reset_index(0,drop=True)