Lære That's All? | Preprocessing Data: Part II

So, seems like all the columns are fine now. Let's double-check if we have converted dates properly.


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# 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!

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Seksjon 2. Kapittel 6

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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!

Alt var klart?

Takk for tilbakemeldingene dine!

Seksjon 2. Kapittel 6