Pandas Extract Number from String

Pandas Extract Number from String

You can extract numbers from strings in a Pandas DataFrame using regular expressions or by splitting the strings and then converting the resulting substrings to numbers. Here are both approaches:

  • Using Regular Expressions:

You can use the str.extract() method with a regular expression to extract numbers from strings.

import pandas as pd # Create a sample DataFrame with strings containing numbers data = {'text': ['abc123def', '456xyz789', 'abc456']} df = pd.DataFrame(data) # Extract numbers using regular expressions df['numbers'] = df['text'].str.extract(r'(\d+)').astype(float) print(df)

In this example, the regular expression r'(\d+)' matches sequences of digits. The str.extract() method returns the extracted substring(s) containing the digits. You can then convert the extracted substring to a numeric value using .astype(float).

  • Using Split and Conversion:

You can split the strings on non-numeric characters and then convert the resulting substrings to numbers.

import pandas as pd # Create a sample DataFrame with strings containing numbers data = {'text': ['abc123def', '456xyz789', 'abc456']} df = pd.DataFrame(data) # Extract numbers by splitting and converting df['numbers'] = df['text'].str.split(r'\D+').str[-1].astype(float) print(df)

In this example, str.split(r'\D+') splits the string on non-digit characters. The .str[-1] extracts the last item from the resulting list of substrings. Finally, .astype(float) converts the substring to a numeric value.

Both methods will extract numbers from strings in your DataFrame and store them in a new column called 'numbers'. Choose the method that best suits your specific use case and the structure of your data.

Examples

  1. How to extract numbers from a string in Pandas? Description: This query aims to find a method to extract numerical values from strings stored in Pandas DataFrame columns.

    import pandas as pd import re # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract numbers using regular expressions df['numbers'] = df['text'].apply(lambda x: re.findall(r'\d+', x)) print(df)

  2. Extract digits from string in Pandas DataFrame? Description: This query seeks a way to extract digit sequences from strings within a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract digits using Pandas' str.extract method df['numbers'] = df['text'].str.extract(r'(\d+)') print(df)

  3. Pandas: How to parse numeric values from strings? Description: This query explores techniques to parse numerical values from strings in Pandas DataFrames.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Parse numeric values using Pandas' str.extract method df['numbers'] = df['text'].str.extract(r'(\d+)', expand=False) print(df)

  4. Python Pandas: Extract integers from string? Description: This query focuses on extracting integer values from strings stored in a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract integers using regular expressions df['numbers'] = df['text'].str.findall(r'\b\d+\b').apply(lambda x: list(map(int, x))) print(df)

  5. Extract numeric values from string in Pandas? Description: This query looks for a method to extract numeric values from strings within a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract numeric values using regular expressions df['numbers'] = df['text'].str.findall(r'\d+').apply(lambda x: list(map(int, x))) print(df)

  6. Pandas: Extract numbers from string column? Description: This query seeks guidance on how to extract numbers from a specific column containing strings in a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract numbers using Pandas' str.extractall method df['numbers'] = df['text'].str.extractall(r'(\d+)').astype(int).groupby(level=0)[0].apply(list) print(df)

  7. How to separate numbers from text in Pandas DataFrame? Description: This query focuses on separating numeric values from text within a column of a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Separate numbers from text using Pandas' str.extract method df['numbers'] = df['text'].str.extract(r'(\d+)') print(df)

  8. Python Pandas: Extract integers from string column? Description: This query aims to extract integer values from a specific column containing strings in a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract integers using Pandas' str.extract method df['numbers'] = df['text'].str.extract(r'(\d+)').astype(float).astype('Int64') print(df)

  9. Pandas: How to retrieve numbers from string data? Description: This query looks for methods to retrieve numeric values from string data stored in a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Retrieve numbers using regular expressions df['numbers'] = df['text'].str.findall(r'\d+').apply(lambda x: list(map(int, x))) print(df)

  10. Extract numerical values from string column in Pandas? Description: This query inquires about extracting numerical values from a specific column containing strings in a Pandas DataFrame.

    import pandas as pd # Sample DataFrame with strings containing numbers df = pd.DataFrame({'text': ['abc 123 def', '456 xyz', '789']}) # Extract numerical values using regular expressions df['numbers'] = df['text'].str.findall(r'\d+').apply(lambda x: list(map(int, x))) print(df)

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