Cara menggunakan reverse table in python

In this article, we will learn how to reverse a row in a pandas data frame using Python. 

With the help of Pandas, we can perform a reverse operation by using loc[], iloc[], reindex[], slicing, and indexing on a row of a data set. 

Creating Dataframe

Let’s create a simple data frame with a dictionary, say column names are: ‘Income’, ‘Expenses’, ‘Profit’.

Python3

import pandas as pd

data = {'Income': [150000, 13000, 11000, 11000],

        'Expenses': [10000, 11000, 7000, 50000],

        'Profit': [5000, 2000, 4000, 6000]

        }

dataframe = pd.DataFrame[data]

dataframe

Output:

Using iloc[] function to Reverse Row

Reversing the rows of a data frame in pandas can be done in python by invoking the iloc[] function.  Let us know how to reverse the rows of a data frame in pandas.

Syntax: DataFrame.iloc[]

Parameters: Index Position: Index position of rows in integer or list of integer.

Return: Data frame or Series depending on parameters

Python3

Data_reverse_row_1 = dataframe.iloc[::-1]

Data_reverse_row_1

Output:

reversed database

Using loc[] function to Reverse Row

Reversing the rows of a data frame in pandas can be done in python by invoking the loc[] function. The panda’s dataframe.loc[] attribute accesses a set of rows and columns in the given data frame by either a label or a boolean array.

Syntax: DataFrame.loc[]

Parameter : None

Returns : Scalar, Series, DataFrame

Python3

Data_reverse_row_2 = dataframe.loc[::-1]

Data_reverse_row_2

Output:

Note: .loc[] and .iloc[] use the indexers to select for indexing operators.

Using reindex[] function to Reverse Row

Reverse rows of the data frame using reindex[] Function. The pandas dataframe.reindex[] function concatenates the dataframe to a new index with optional filling logic, placing NA/NaN at locations that have no value in the previous index.

Syntax: DataFrame.reindex[index=None]

Parameter : index, columns : New labels / index to conform to. Preferably an Index object to avoid duplicating data

Returns : reindexed : DataFrame

Python3

df.reindex[index=dataframe.index[::-1]]

Output:

Using dataframe indexing to Reverse Row

Reverse rows using data frame indexing in python. In Python, we can set the index of a dataframe in reverse. In this method, we create a Python list and pass it’s an index to the dataframe[] function’s index parameter. Let’s implement this through Python code.

Syntax: DataFrame[start:end:slicing]

Python3

Output:

Using the reset_Index[] function to Reverse Row

Here we use the reset_index[] function to reset the index for the entire database and also pass Drop=True to drop all old indices.

Python3

d = dataframe.loc[::-1].reset_index[drop=True].head[]

print[d]

Output:

reversed database