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How to change the names of Columns in Python

Introduction

To play with huge amounts of data, in Python we require a tool. The tool which is available in Python is Pandas. Pandas is an open-source library. It is used to analyze huge datasets without any difficulty. This is the biggest advantage of Pandas.

By using Pandas, a Data Frame can be created. A Data Frame is a table which contains all the contents of a dataset. This Data Frame helps us to visualize the ugly looking dataset into a good-looking table. So, now let us learn about how to convert the data types of the contents present in the dataset.

Creation of Data Frames

To create a Data Frame, there are few steps. They are

1. Install Pandas (ignore if available)

The command to install Pandas is

pip install pandas

or

python m pip install pandas

2. Open Python idle window or any Python compiler

3. The first thing we have to do is to import Pandas

We can import Pandas into the program with a command import Pandas as pd

4. Create a dictionary or list or tuple for creating a Data Frame. If we have a dataset we export it into the program with a command like

ds = pd.read_csv(‘File-Name’)

5. Now with a command like

df = pd.DataFrame(dict_name/tuple_name/list_name,columns=’Col_1’,’Col_2’….)

Example:

'''
1.) downloaded pandas library
2.) Opened pandas library
3.) Import pandas library
'''


import pandas as pd


# 4.) A Dataset needs to be created


DataSet={
‘Players’: ['Root','Smith','Kohli','Kane'],
‘Matches’: [24,11,15,6],
‘Runs’: [2595, 779,756,491],
‘AVG’ :[60.25,45.82,29.07,49.10],
‘100s’: [11,1,0,1]
}
#5.) Data Frame Creation
df = pd.DataFrame(DataSet)


print(df)

Output:

Players  Matches  Runs    AVG  100s
0    Root       24          2595  60.25    11
1   Smith       11          779  45.82     1
2   Kohli       15           756  29.07     0
3    Kane        6           491  49.10     1

Now we have created a Data set and also a Data Frame using pandas. Now let us know how to change the names of the rows using some pre-defined methods.

The ways to change the names of columns are:

1. Changing the Name of Column using a Method Columns

This is one of the methods used to change the names columns. This is in-built method used in Data Frames.

Syntax:

DataFrame_name.columns [‘col1_name’, ‘col2_name’,…………………]

Example:

Let us apply this method to the previous data set created.

print(df)


df.columns =['Sportsmen' , 'Matches_Played' , 'Runs_Scored' , 'Average' , 'Centuries' ]
print(df)

Output:

  Players  Matches  Runs    AVG  100s
0    Root       24        2595  60.25    11
1   Smith       11       779    45.82        1
2   Kohli       15         756   29.07       0
3    Kane        6         491   49.10        1
  Sportsmen  Matches_Played  Runs_Scored  Average  Centuries
0      Root              24         2595    60.25         11
1     Smith              11          779    45.82          1
2     Kohli              15          756    29.07          0
3      Kane               6          491    49.10          1

Explanation:

The above output shows the change in the names of the columns.

Here,

Players -> Sportsmen
Matches -> Matches_Played
Runs -> Runs_Scored
AVG -> Average
100s -> Centuries

This is how this method is used to change the names of the columns

2. Rename Method

This is also in-built method present in a Data Frame. This method is also used to change the name columns present in the Data Frame

Syntax:

Data Frame name = Data Frame name .rename( columns = {‘old column name1’ : ‘new column name1}, ‘ old column name 2’ ,’ new columns name 2 } )

Example:

We are again using the same Data Frame created previously.

print(df)


df=df.rename( columns={'AVG': 'Average','100s':'Centuries'})


print(df)

Output:

  Players  Matches  Runs    AVG  100s
0    Root       24  2595  60.25    11
1   Smith       11   779  45.82     1
2   Kohli       15   756  29.07     0
3    Kane        6   491  49.10     1
  Players  Matches  Runs  Average  Centuries
0    Root       24  2595    60.25         11
1   Smith       11   779    45.82          1
2   Kohli       15   756    29.07          0
3    Kane        6   491    49.10          1

This method is more convenient than previous method. This is because in the previous columns method we have to convert all the old column names to new column names.

Whereas in this rename method we can convert only specified column names with mentioning them.

3. Using Indexing Method

Here in this method, we will directly approach the column and change its method with the help assignment operator.

Syntax:

Data Frame Name. column.values[index value] =’ new column name’

Example:

print(df)


df.columns.values[3] = 'Average'
print(df)

Output:

Players  Matches  Runs    AVG  100s
0    Root       24  2595  60.25    11
1   Smith       11   779  45.82     1
2   Kohli       15   756  29.07     0
3    Kane        6   491  49.10     1
  Players  Matches  Runs  Average  100s
0    Root       24  2595    60.25    11
1   Smith       11   779    45.82     1
2   Kohli       15   756    29.07     0
3    Kane        6   491    49.10     1

These are the ways through which we can change the names of columns in python.



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