I have a dataframe like this:
>>> df = pd.DataFrame({ 'Date': [ pd.to_datetime("2022-07-01"), pd.to_datetime("2020-07-02"), pd.to_datetime("2020-07-03"), ], "Price": [ {24.9, 23.0, 22.5, 23.5}, {24.9, 25.0, 26.5, 23.7}, {25.2, 24.5, 23.6, 23.8}, ]}) >>> df Date Price 0 2022-07-01 {24.9, 23.5, 22.5, 23.0} 1 2020-07-02 {24.9, 25.0, 26.5, 23.7} 2 2020-07-03 {24.5, 25.2, 23.8, 23.6}
I want to add a new column ‘intersec’ and get the intersection of the Price column and its shift value. But when I use
df['intersec'] = df.price[1:]&df.price.shift()[1:]
It doesn’t work, I get the following error:
TypeError: unsupported operand type(s) for &: 'set' and 'bool'
what should I do? My expected result is:
>>> df Date Price intersec 0 2022/7/1 {24.9, 23.5, 22.5, 23.0} NaN 1 2020/7/2 {24.9, 25.0, 26.5, 23.7} 24.9 2 2020/7/3 {24.5, 25.2, 23.8, 23.6} NaN
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Answer
shift the price
df["shifted_price"] = df.Price.shift()
find intersect
df["intersec"] = df[1:].apply(lambda x: list(set(x["Price"]) & set(x["shifted_price"])), axis=1)
sample output
Date Price shifted_price intersec 0 2022-07-01 {24.9, 23.5, 22.5, 23.0} NaN NaN 1 2020-07-02 {24.9, 25.0, 26.5, 23.7} {24.9, 23.5, 22.5, 23.0} [24.9] 2 2020-07-03 {24.5, 25.2, 23.8, 23.6} {24.9, 25.0, 26.5, 23.7} []