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This article mainly explains "R language and the common application of sorting function in Python". Interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn the R language and the common sorting function applications in Python.

Sorting may be a high-frequency application in the daily data cleaning process. Today this article introduces the most common sorting function applications in R language and Python.

R language:

Sort

Order

Rank

Arrange

Sorting uses different functions according to the sorting of vectors and data boxes. Of the above four functions, the first three are for vectors and the last one is for data boxes.

Sort

X%plyr::arrange (class,-value)

Arrange function can not only sort multivariable rules, but also specify descending order only with minus sign. The syntax is concise and powerful. When multivariable, classification variables are generally the first, continuous variables are the last, coarse-grained dimensions are the first, and the sorting granularity of classification variables is decreasing in turn. Finally, there are continuous variables.

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Python:

-

Sort

Sorted

.sort _ index

.sort _ value

List sorting method:

X = [97, 93, 85, 74, 32, 100, 99, 67]

For the sorting of list, Python provides a global sorted function and list's own sort function to complete the sorting function.

Sorted (x) # default birth order

Sorted (xthecontrolling true) # specifies the descending order

X.sort () # default birth order

X.sort (reverse=True) # specify descending order

Dictionary sorting method:

Mydata= {"A": 97, "B": 93, "C": 85, "D": 74, "E": 32, "F": 100, "G": 99, "H": 67}

Sorted (mydata.keys ()) # sort by dictionary key

Sorted (mydata.keys (), reverse=True) # sorts inversely according to the keys of the dictionary

Sort by key value pair:

Sorted (mydata.items (), key=lambda item:item [1]) # sorted according to the order of value fields

Sorted (mydata.items (), key=lambda item:item [1], reverse=True) # in reverse order according to the value field

Sort the data boxes:

Import pandas as pd

Import numpy as np

Df1=pd.DataFrame ({"id": [1001 id 1002 1003 1004 1005 1006 1007 1008]

"gender": ['male','female','male','female','male','female','male','female']

"pay": ['Yoshimachi, naughty, naughty, nasty, nasty.

"m-point": [10, 12, 20, 20, 40, 40, 40, 40, 30, 20])

The data boxes generated by pandas also have sort methods.

Sort by value:

Df1.sort_values (["id"]) # sorts with values

Df1.sort_values (["id"], ascending=False) # descending sort

Df1.sort_values (["pay", "m-point"]) # sort multiple fields

Index sort:

Df1=df1.set_index ('id') # set the index column

Df1.sort_index () # sorting using indexes

Df1.sort_index (ascending=False) # sort in descending order using index columns

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Summary of this section:

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Sort function:

R language:

Vector:

Sort

Order

Rank

Data box:

Arrange

Python:

Lists and dictionaries:

Sort

Sorted

Data box:

.sort _ index

.sort _ value

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