Hi, I’m Jiejie

Today I’m going to introduce a super liver product! Pandas is a numpy-based tool that was created to solve data analysis tasks. It provides a large number of functions and methods that allow us to process data quickly and easily. The 20 functions described in this article are absolutely data-processing killers that you’ll love to use.

Construct data set

I’m going to construct a data set for you to demonstrate these 20 functions.

Import pandas as pd df = {' name ': [' huang', 'yellow supreme', 'huang Lao evil', 'Chen Damei', 'sun shangxiang']. ['Huang tong_xue',' Huang ZHI_zun ','Huang Lao_xie','Chen Da_mei',' Sun Shang_xiang '], [' male ','women','men',' female ',' male '], 'ID ':['463895200003128433','429475199912122345','420934199110102311','431085200005230122','420953199509082345'], 'height' : [' _good mid - 175 ', 'low: 165 _bad', 'low: 159 _bad', 'high: 180 _verygood', 'low: 172 _bad']. 'Home Address ':[' Guangshui, Hubei ',' Xinyang, Henan ',' Guilin, Guangxi ',' Xiaogan, Hubei ',' Guangzhou, Guangdong '] 'Telephone Number ':['13434813546','19748672895','16728613064','14561586431','19384683910'], 'income: [' 11000', '8500', '09000', '6500', '20000']} df = pd DataFrame df (df)Copy the code

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1. The cat function

This function is mainly used for concatenating strings;

If (df[" home "] ='-'*3) if (df[" home "] ='-'*3)Copy the code

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2. The contains function

This function is used to determine whether a string contains a given character.

Df [" home address "].str. Contains (" wide ")</pre>Copy the code

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3. Startswith, endswith functions

This function is used to determine if a string begins with… Beginning/ending;

# "29" is the first line Spaces at the beginning of df [r]. "name" STR. Startswith (" yellow ") df [r]. "English name" STR. Endswith (" e ") < / pre >Copy the code

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4. The count function

This function counts the number of occurrences of a given character in a string.

Df [" phone number "].str.count("3")</pre>Copy the code

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5. The get function

This function is used to get a string at a specified position;

Df (" name "). The STR. Get (1) df [r]. "height" STR. The split (" : ") df [r]. "height" STR. The split (" : "). STR. Get (0) < / pre >Copy the code

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6. The len function

This function is mainly used to calculate the length of a string;

Df [r]. "gender" STR. Len () < / pre >Copy the code

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7. Upper and lower functions

This function is mainly used for English case conversion;

Df ["英文名 称 "].str.upper() df["英文名 称 "].str.lower()</pre>Copy the code

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8. Pad +side argument /center function

This function is mainly used to add a given character to the left, right, or left of a string;

Df [r]. "home address" STR. The pad (# 10, fillchar = "*") is equivalent to ljust (df) [r]. "home address" STR. Pad (10, side = "right", fillchar = "*") # equivalent rjust () Df [" home address "].str. Center (10,fillchar="*")</pre>Copy the code

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9. Repeat function

This function is mainly used to repeat the string several times;

Df [r]. "gender" STR. Repeat (3) < / pre >Copy the code

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10. Slice_replace function

This function is used to replace characters at a specified position with a given string.

Df [" phone number "].str.slice_replace(4,8,"*"*4)</pre>Copy the code

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11. The replace function

This function is used to replace a character at a specified position with a given string.

Df (" height "). The STR. Replace (" : ", "-") < / pre >Copy the code

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This function also takes a regular expression that replaces the character at the specified position with the given string.

Df [" income "].str.replace("\d+\.\d+"," re ")</pre>Copy the code

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12. Split method +expand parameter

This function is mainly used to expand a column into several columns;

# df[" height "].str.split(":") Expand (":",expand=True) df # split expand= join Df (" height "). The STR. The split (" : "). The STR. Join ("?" *5)</pre>Copy the code

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Strip, rstrip, lstrip function

This function is mainly used to remove whitespace, newline characters;

Df (" name "). The STR. Len (df) (" name ") = df [r]. "name" STR. The strip (df) [r]. "name" STR. Len () < / pre >Copy the code

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14. The.findall function

This function is mainly used to use regular expressions to remove matches in strings and return a list of search results.

Df [" height "].str.findall("[a-za-z]+")</pre>Copy the code

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15. Extract, Extractall function

This function takes the regular expression and extracts the matching string (always in parentheses);

Df (" height "). The STR. Extract (" ([a zA - Z] +) ") # extractall extraction to get composite index df [r]. "height" STR. Extractall (" ([a zA - Z] +) ") # extract collocation expand parameters Df [r]. "height" STR. Extract (" ([a zA - Z] +). *? ([a-zA-Z]+)",expand=True)</pre>Copy the code

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