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Pandas Percentage of Total with Groupby
Calculating the percentage of sales per office in a given state can be done using Pandas' groupby. However, it requires an additional step to achieve the desired result.
Suppose we have a CSV file with columns representing State, Office ID, and Sales. We can import Pandas and create a DataFrame:
import pandas as pd df = pd.DataFrame({'state': ['CA', 'WA', 'CO', 'AZ'] * 3, 'office_id': list(range(1, 7)) * 2, 'sales': [np.random.randint(100000, 999999) for _ in range(12)]})
To calculate the total sales for each office and state, we can group by those columns:
state_office = df.groupby(['state', 'office_id']).agg({'sales': 'sum'})
To calculate the percentage of sales per office in a given state, we can group by the state and apply a function that divides each office's sales by the total state sales:
state_pcts = state_office.groupby(level=0).apply(lambda x: 100 * x / float(x.sum()))
This results in a DataFrame with the percentage of sales for each office:
print(state_pcts) sales state office_id AZ 2 16.981365 4 19.250033 6 63.768601 CA 1 19.331879 3 33.858747 5 46.809373 CO 1 36.851857 3 19.874290 5 43.273852 WA 2 34.707233 4 35.511259 6 29.781508
This method effectively calculates the percentage of sales per office in a given state by "reaching up" to the state level of the groupby to total up the sales for the entire state.
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