That's All?
So, seems like all the columns are fine now. Let's double-check if we have converted dates properly.
123456789101112131415# 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') # Displaying first four dates before converting print(df['Date'].head(4)) # Change column type df['Date'] = pd.to_datetime(df['Date'], dayfirst = True) # Displaying first four dates and dtypes of dataframe print(df['Date'].head(4)) print(df.dtypes)
Yes, this time everything seems to be fine. Dtypes of the dataframe are appropriate, so we are ready to make some analysis and visualizing!
Kiitos palautteestasi!
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Completion rate improved to 3.45That's All?
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So, seems like all the columns are fine now. Let's double-check if we have converted dates properly.
123456789101112131415# 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') # Displaying first four dates before converting print(df['Date'].head(4)) # Change column type df['Date'] = pd.to_datetime(df['Date'], dayfirst = True) # Displaying first four dates and dtypes of dataframe print(df['Date'].head(4)) print(df.dtypes)
Yes, this time everything seems to be fine. Dtypes of the dataframe are appropriate, so we are ready to make some analysis and visualizing!
Kiitos palautteestasi!
