Stopping a forward fill based on a different string column changing in the DF

Question

i'm new to Python so go easy!

I have a Dataframe like the following. I would like to forward fill the NaN's in the shares_owned column but stop when the string in df['ticker'] changes. And only start when another number appears in shares_owned again.

date	ticker	shares_owned	price
01/01/2020	EZY	NaN	£2
02/01/2020	EZY	10	£2.1
03/01/2020	EZY	NaN	£2.12
04/01/2020	EZY	NaN	£12.5
01/01/2020	FTSE	NaN	£11
02/01/2020	FTSE	NaN	£12
03/01/2020	FTSE	2	£12.5
04/01/2020	FTSE	NaN	£12.5

For example, the output table would look like this:

date	ticker	shares_owned	price
01/01/2020	EZY	NaN	£2
02/01/2020	EZY	10	£2.1
03/01/2020	EZY	10	£2.12
04/01/2020	EZY	10	£12.5
01/01/2020	FTSE	NaN	£11
02/01/2020	FTSE	NaN	£12
03/01/2020	FTSE	2	£12.5
04/01/2020	FTSE	2	£12.5

So far I have been trying to use the .fillna(method='ffill') to no avail.

Answer 1

• you note groups, hence groupby() does the grouping
• within the group fillna(method="fill") within a transform()

df = pd.read_csv(io.StringIO("""date    ticker  shares_owned    price
01/01/2020  EZY NaN £2
02/01/2020  EZY 10  £2.1
03/01/2020  EZY NaN £2.12
04/01/2020  EZY NaN £12.5
01/01/2020  FTSE    NaN £11
02/01/2020  FTSE    NaN £12
03/01/2020  FTSE    2   £12.5
04/01/2020  FTSE    NaN £12.5"""), sep="\t")

df["shares_owned"] = df.groupby("ticker")["shares_owned"].transform(lambda s: s.fillna(method="ffill"))

output

	date	ticker	shares_owned	price
0	01/01/2020	EZY	nan	£2
1	02/01/2020	EZY	10	£2.1
2	03/01/2020	EZY	10	£2.12
3	04/01/2020	EZY	10	£12.5
4	01/01/2020	FTSE	nan	£11
5	02/01/2020	FTSE	nan	£12
6	03/01/2020	FTSE	2	£12.5
7	04/01/2020	FTSE	2	£12.5