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What is astype() in pandas?

Eman Kashif

pandas is an open-source Python library that provides functionalities to manipulate and analyze data. It is used widely in machine learning to inspect data and extract useful information. This allows for the most appropriate model to be applied to the dataset.

pandas provides an astype() function which casts a pandas object to the specified dtype to keep the data type consistent.

Syntax

DataFrame.astype(dtype, copy=True, errors='raise')

Arguments

  1. dtype: This specifies the data type. It can also be a dictionary with data types for each of the columns.
  2. copy: This can be set to True or False. If it is set to True, a copy will be returned instead of changes being made to the original data frame. The default is set to True. (Optional)
  3. errors: They can be set to raise or ignore. Any errors that may come up are ignored if they are set to ignore. The default is set to raise. (Optional)

Return value

The function returns a pandas data frame object that has the changed data types.

Example code

#import library
import pandas as pd

#initialize data
data = {
  "Time": [45, 56, 49, 64, 53],
  "Steps": [134, 153, 178, 205, 186],
  "Calories": [284.5, 234.5, 291.4, 251.0, 211.7]
}

#create a data frame
df = pd.DataFrame(data)

#print data frame
print(df)

We pass a dictionary as an argument in order to change the data type of all the columns separately. The dictionary contains the column names and the respective dtypes to which we want to change.

#change the data types of all the columns
new_df = df.astype({
  'Time': 'float',
  'Steps': 'float',
  'Calories': 'int64'})

#print new data frame
print(new_df)

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