Date Range
Good, we know the best selling stores for entire date range. But how wide it is? Let's find out.
Since we convert the 'Date'
column into the datetime
type, we can apply different methods on it, like .min()
or .max()
. They will return the earliest and the latest dates in the column.
123456789# Loading the library import pandas as pd # Reading the data df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/72be5dde-f3e6-4c40-8881-e1d97ae31287/shops_data3.csv') df['Date'] = pd.to_datetime(df['Date'], dayfirst = True) # Inspecting the 'Date' column print(df['Date'].min())
For the following question, feel free to edit the code above if necessary.
Obrigado pelo seu feedback!
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Date Range
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Good, we know the best selling stores for entire date range. But how wide it is? Let's find out.
Since we convert the 'Date'
column into the datetime
type, we can apply different methods on it, like .min()
or .max()
. They will return the earliest and the latest dates in the column.
123456789# Loading the library import pandas as pd # Reading the data df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/72be5dde-f3e6-4c40-8881-e1d97ae31287/shops_data3.csv') df['Date'] = pd.to_datetime(df['Date'], dayfirst = True) # Inspecting the 'Date' column print(df['Date'].min())
For the following question, feel free to edit the code above if necessary.
Obrigado pelo seu feedback!