CODEWITHSUNDEEP
pythonpandas
orange123
orange123

Reputation: 75

Python - How to create a new dataframe for each month out of a list of data

I have a list of stock data over the years and I want to remove the bottom x% in terms of market cap in each month. My idea is to make a loop that creates a new Pandas dataframe for each month, and then within that month, I remove the bottom x% in terms of market cap. This is what the data looks like

enter image description here

Upvotes: 0

Views: 639

Answers (1)

Ynjxsjmh
Ynjxsjmh

Reputation: 30052

df['date'] = pd.to_datetime(df['date'])
df['year-month'] = df['date'].map(lambda x: x.strftime('%Y-%m'))

df = df.sort_values(['year-month', 'MarketCap'], ascending=[True, False])

df = df.groupby('year-month').apply(lambda x: x[x['MarketCap'] > x['MarketCap'].quantile(.1)]).reset_index(1, drop = True)

df = df.drop(columns=['year-month']).reset_index().drop(columns=['year-month'])

First create a column contains only year and month.

Then sort year-month and MarketCap column ascending and descending.

Group by MarketCap column and filter out the row below 10% in each group.

Upvotes: 1

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