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Oppiskele Changing the Data Type | Brief Introduction
Data Preprocessing

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Changing the Data Type

You already know how to change the data type from string to number, for example. But let's take a closer look at this small but important task.

Let's start by changing the data type from string to datetime. Most often, you will need this to work with time series. You can perform this operation using the .to_datetime() method:

To convert a string to a bool - use the .map() method on the column whose values you want to change:

For example, if you have a price column that looks like "$198,800" and you want to turn it into a float - you should create custom transformation functions:

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import pandas as pd import re # Create simple dataset df = pd.DataFrame(data={'Price':['$4,122.94', '$1,002.3']}) # Create a custom function to transform data # x - value from column def price2int(x): return float(re.sub(r'[\$\,]', '', x)) # Use custom transformation on a column df['Price'] = df['Price'].apply(price2int)
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Tehtävä

Swipe to start coding

Read the sales_data_types.csv dataset and change the data type in the Active column from str to bool.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
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book
Changing the Data Type

You already know how to change the data type from string to number, for example. But let's take a closer look at this small but important task.

Let's start by changing the data type from string to datetime. Most often, you will need this to work with time series. You can perform this operation using the .to_datetime() method:

To convert a string to a bool - use the .map() method on the column whose values you want to change:

For example, if you have a price column that looks like "$198,800" and you want to turn it into a float - you should create custom transformation functions:

12345678910111213
import pandas as pd import re # Create simple dataset df = pd.DataFrame(data={'Price':['$4,122.94', '$1,002.3']}) # Create a custom function to transform data # x - value from column def price2int(x): return float(re.sub(r'[\$\,]', '', x)) # Use custom transformation on a column df['Price'] = df['Price'].apply(price2int)
copy
Tehtävä

Swipe to start coding

Read the sales_data_types.csv dataset and change the data type in the Active column from str to bool.

Ratkaisu

Switch to desktopVaihda työpöytään todellista harjoitusta vartenJatka siitä, missä olet käyttämällä jotakin alla olevista vaihtoehdoista
Oliko kaikki selvää?

Miten voimme parantaa sitä?

Kiitos palautteestasi!

close

Awesome!

Completion rate improved to 3.33

Pyyhkäise näyttääksesi valikon

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