Impara 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!

Tutto è chiaro?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 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!

Tutto è chiaro?

Grazie per i tuoi commenti!

Sezione 2. Capitolo 6