How to Extract Substring From Pandas Column?

To extract a substring from a pandas column, you can use the str.extract() method in pandas. This method allows you to specify a regular expression pattern to extract the substring from each value in the column. You can also use slicing or other string manipulation methods to extract a substring based on a specific position or length. Additionally, you can use the str.contains() method to filter rows based on whether a substring is present in the column values. These methods are helpful for data cleaning, text processing, and extracting specific information from your data.

How to extract text after a certain word in pandas column?

You can extract text after a certain word in a pandas column by using the str.extract method with a regular expression. Here's an example of how to extract text after the word "apple" in a column called "fruits":

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import pandas as pd

# Sample DataFrame
df = pd.DataFrame({'fruits': ['I like apple pie', 'apple is my favorite fruit']})

# Extract text after the word "apple"
df['after_apple'] = df['fruits'].str.extract(r'apple(.*)')

print(df)

This will create a new column called "after_apple" in the DataFrame df which contains the text that comes after the word "apple" in each row of the "fruits" column. The regular expression apple(.*) matches the word "apple" and captures everything that follows it into a separate group.

How to extract substring from pandas column and concatenate with another column?

You can extract a substring from a pandas column using the str.extract method and concatenate it with another column using the + operator. Here's an example:

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import pandas as pd

# Create a sample dataframe
data = {'text': ['ABC123', 'DEF456', 'GHI789'],
        'number': [1, 2, 3]}
df = pd.DataFrame(data)

# Extract substring from 'text' column
df['substring'] = df['text'].str.extract(r'([A-Z]+)')

# Concatenate 'substring' column with 'number' column
df['combined'] = df['substring'] + df['number'].astype(str)

print(df)

This will output:

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    text  number substring combined
0  ABC123       1       ABC      ABC1
1  DEF456       2       DEF      DEF2
2  GHI789       3       GHI      GHI3

In this example, we extracted the uppercase letters from the 'text' column using a regular expression pattern and stored it in a new column called 'substring'. We then concatenated the 'substring' column with the 'number' column and stored the result in a new column called 'combined'.

What is the purpose of str.extractall() method in pandas?

The purpose of the str.extractall() method in pandas is to extract all occurrences of a regex pattern in each element of a Series and create a multi-index DataFrame where the first level is the row index and the second level is the match index. This allows you to extract multiple matches from a single string and store them in a structured format for further analysis.

How to extract uppercase letters from pandas column?

To extract uppercase letters from a pandas column, you can use the str.contains() method along with a regular expression to filter out only the uppercase letters. Here's an example:

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import pandas as pd

# Create a sample pandas DataFrame
data = {'text': ['Hello', 'World', 'Python', 'DataScience']}
df = pd.DataFrame(data)

# Extract uppercase letters from the 'text' column
uppercase_letters = df['text'].str.extractall('([A-Z]+)').unstack().apply(lambda x: ''.join(x.dropna()), axis=1)

print(uppercase_letters)

This code snippet will extract and print the uppercase letters from the 'text' column in the DataFrame. You can adjust the regular expression pattern '([A-Z]+)' to match your specific criteria for extracting uppercase letters.