How to Replace Subset Of String From Pandas?

To replace a subset of strings in a pandas DataFrame, you can use the str.replace() method. This method allows you to specify the substring you want to replace and the new string you want to replace it with. Simply call this method on the column containing the strings you want to replace and pass in the appropriate arguments. This will update the DataFrame with the new strings. Keep in mind that the str.replace() method is case-sensitive, so make sure you specify the correct substring to replace.

How to substitute part of a string in pandas column?

You can use the .str.replace() method in pandas to substitute part of a string in a column. Here's an example:

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import pandas as pd

# Create a sample dataframe
data = {'col1': ['apple pie', 'banana bread', 'cherry cobbler']}
df = pd.DataFrame(data)

# Substitute 'apple' with 'blueberry' in the col1 column
df['col1'] = df['col1'].str.replace('apple', 'blueberry')

print(df)

This will output:

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                col1
0       blueberry pie
1      banana bread
2   cherry cobbler

You can also use regular expressions with the .str.replace() method for more complex string substitutions.

How to change part of a string in pandas column?

You can change part of a string in a pandas column using the str.replace() function. Here's an example:

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import pandas as pd

# create a sample DataFrame
data = {'text': ['hello world', 'Python is great', 'data science']}
df = pd.DataFrame(data)

# replace part of the string in the 'text' column
df['text'] = df['text'].str.replace('great', 'awesome')

print(df)

In this example, we are replacing the word "great" with "awesome" in the 'text' column of the DataFrame. You can customize the str.replace() function parameters to replace any substring with another substring in your DataFrame column.

How to replace multiple instances of a string in pandas series?

You can replace multiple instances of a string in a pandas series using the str.replace() method. Here is an example of how you can do this:

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import pandas as pd

# Create a pandas series
data = {'col1': ['foo bar foo', 'foo foo', 'bar foo bar']}
df = pd.DataFrame(data)

# Replace multiple instances of a string in the series
df['col1'] = df['col1'].str.replace('foo', 'baz')

print(df)

This will replace all instances of the string 'foo' in the series with 'baz'. You can specify multiple strings to replace by passing a dictionary to the str.replace() method with the strings to be replaced as keys and the strings to replace them with as values.

How to replace a pattern in pandas dataframe?

To replace a pattern in a Pandas DataFrame, you can use the replace() method along with regular expressions.

Here's an example of how you can replace a pattern in a Pandas DataFrame:

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import pandas as pd

# Create a sample DataFrame
data = {'col1': ['apple', 'banana', 'grape', 'orange', 'melon'],
        'col2': ['10 USD', '20 EUR', '15 USD', '30 GBP', '25 EUR']}
df = pd.DataFrame(data)

# Replace 'USD' with 'Dollar' in col2
df['col2'] = df['col2'].str.replace(r'USD', 'Dollar')

print(df)

This will output:

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     col1       col2
0   apple   10 Dollar
1  banana      20 EUR
2   grape   15 Dollar
3  orange      30 GBP
4   melon      25 EUR

In this example, we used the replace() method with a regular expression r'USD' to replace the pattern 'USD' with 'Dollar' in the 'col2' column of the DataFrame.