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Pandas str.wrap()
is an important technique when working with long text data (paragraphs or messages). This is used to spread long text data onto new lines, or to handle whitespace when it exceeds the passed width. Since this is a string method, you must prefix .str before calling this method.
Syntax: Series .str.wrap (width, ** kwargs)
Parameters:
width: Integer value, defines maximum line width** kwargs [Optional parameters]
expand_tabs: Boolean value, expands tab characters to spaces if True
replace_whitespace: Boolean value, if true, each white space character is replaced by single white space.
drop_whitespace: Boolean value, If true, removes whitespace if any at the beginning of new lines
break_long_words: Boolean value, if True, breaks word that are longer than the passed width.
break_on_hyphens: Boolean value, if true, breaks string on hyphens where string length is less than width.Return type: Series with splitted lines / added characters (’’)
To load dataset used in code press here.
In the following examples, the data frame used contains data for some NBA players. An image of the data frame before any operations is attached below.
Example:
In this example, the Team wrapped 5 characters wide. Therefore, / n will appear after every 5 characters. A random item from the new team column and the old team column is printed to see the work. Before any operations are applied, null elements are removed using .dropna()
.
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Output:
As shown in the output images, the new column has & # 39; / n & # 39; after every 5 characters. After printing the same index of the old and new command columns, you can see that without adding a newline character in the print statement, python automatically reads & # 39; / n & # 39; in a line and places it on a new line.
Data frame with New Team column
Exit :
Los Angeles Lakers ------------ Los A ngele s Lak ers
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San Francisco | 2023-02-07
I was preparing for my coding interview, thanks for clarifying this - Python | Pandas Series.str.wrap () in Python is not the simplest one. Will use it in my bachelor thesis
Tallinn | 2023-02-07
Thanks for explaining! I was stuck with Python | Pandas Series.str.wrap () for some hours, finally got it done 🤗. Will get back tomorrow with feedback
California | 2023-02-07
Maybe there are another answers? What Python | Pandas Series.str.wrap () exactly means?. Will get back tomorrow with feedback