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Pandas is a popular data analysis library in Python that provides various methods for manipulating and converting data. One of the common tasks in data analysis is converting strings to float values, which is often necessary for performing mathematical operations. In Pandas, this can be achieved by using the astype() method, which allows users to specify the desired data type for a particular column or series. By using this method, strings can be easily converted to float values, making them suitable for further analysis and calculations.
Convert Strings to Float in Pandas
You can use the following methods to convert a string to a float in pandas:
Method 1: Convert a Single Column to Float
#convert "assists" column from string to float df['assists'] = df['assists'].astype(float)
Method 2: Convert Multiple Columns to Float
#convert both "assists" and "rebounds" from strings to floats df[['assists', 'rebounds']] = df[['assists', 'rebounds']].astype(float)
Method 3: Convert All Columns to Float
#convert all columns to float df = df.astype(float)
The following examples show how to use each method in practice with the following pandas DataFrame:
import numpy as np import pandas as pd #create DataFrame df = pd.DataFrame({'points': [np.nan, 12, 15, 14, 19], 'assists': ['5', np.nan, '7', '9', '12'], 'rebounds': ['11', '8', '10', '6', '6']}) #view DataFrame df points assists rebounds 0 NaN 5.0 11 1 12.0 NaN 8 2 15.0 7.0 10 3 14.0 9.0 6 4 19.0 12.0 6 #view column data types df.dtypes points float64 assists object rebounds object dtype: object
Example 1: Convert a Single Column to Float
The following syntax shows how to convert the assists column from a string to a float:
#convert "assists" from string to float df['assists'] = df['assists'].astype(float) #view column data types df.dtypes points float64 assists float64 rebounds object dtype: object
Example 2: Convert Multiple Columns to Float
The following syntax shows how to convert both the assists and rebounds columns from strings to floats:
#convert both "assists" and "rebounds" from strings to floats df[['assists', 'rebounds']] = df[['assists', 'rebounds']].astype(float) #view column data types df.dtypes points float64 assists float64 rebounds float64 dtype: object
Example 3: Convert All Columns to Float
The following syntax shows how to convert all of the columns in the DataFrame to floats:
#convert all columns to float df = df.astype(float) #view column data types df.dtypes points float64 assists float64 rebounds float64 dtype: object
Bonus: Convert String to Float and Fill in NaN Values
The following syntax shows how to convert the assists column from string to float and simultaneously fill in the NaN values with zeros:
#convert "assists" from string to float and fill in NaN values with zeros df['assists'] = df['assists'].astype(float).fillna(0) #view DataFrame df points assists rebounds 0 NaN 5.0 11 1 12.0 0.0 8 2 15.0 7.0 10 3 14.0 9.0 6 4 19.0 12.0 6
Additional Resources
The following tutorials explain how to perform other common tasks in pandas: