Get columns from Pandas DataFrame | using columns, values, info, sorted methods

In this chapter of pandas tutorial, we will discuss:

• create dataframe in pandas,
• get column names from pandas dataframe using columns method,
• how to get columns from pandas dataframe using values on columns,
• get columns from pandas dataframe using info(),
• how to get sorted column in pandas,

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Create DataFrame

DataFrame is a 2 dimensional data structure that stores data in 2 dimensional format. One dimension refers to a row and second dimension refers to a column. So it will store data in rows and columns.

 

We can create DataFrame using DataFrame() method. But this is available in pandas module, so we have to import pandas module.

Syntax:

pandas.DataFrame(data)

Where, data is the input dataframe. The data can be a dictionary that stores list of values with specified key

 

Example: create dataframe pandas

In this example, we will create dataframe in pandas with 4 rows and 4 columns with college data

import pandas as pd

#create dataframe from the college data

data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   })

#display the dataframe
print(data)

Output: Below dataframe is created

  college_id       college_name college_address  Total Staff

0      c-001  vignan university          guntur         1200

1      c-021               vvit          guntur         3422

2      c-002           RVR - JC          guntur         5644

3      c-004  Andhra University          guntur          670

Lets start to get columns from pandas dataframe. We will see different methods to do that task.

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Method 1  - get columns from pandas dataframe using columns method

This columns is used to return or get columns from pandas dataframe in a list. It will also return the column datatype i.e object along with column name.

Syntax:

dataframe.columns

where, dataframe is the input dataframe

 

Example: get column names from pandas dataframe using columns method is shown in below code snippet

import pandas as pd

#create dataframe from the college data

data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   })



#display the columns in the dataframe

print(data.columns)

 

Output: We get column names from pandas dataframe below

Index(['college_id', 'college_name', 'college_address', 'Total Staff'], dtype='object')

Lets see another method to get column names from pandas dataframe.

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Method 2 : get columns from pandas dataframe using columns.values

This columns.values is used to return the column names in a list without datatype.

Syntax:

dataframe.columns.values

where, dataframe is the input dataframe

 

Example: extract column names from pandas dataframe using values

In this example, we are using shape function to return number of rows and columns in a tuple from the dataframe.

import pandas as pd

#create dataframe from the college data

data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   })

#display the columns in the dataframe
print(data.columns.values)

Output: we successfully extract column names from pandas dataframe

['college_id' 'college_name' 'college_address' 'Total Staff']

Lets see another method to get columns from pandas dataframe.

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Method 3 : get columns from pandas dataframe using sorted() function

This sorted() function is used to return the column names in a list without datatype in sorted order.

Syntax:

sorted(dataframe)

where, dataframe is the input dataframe

 

Example: Lets see how to get sorted column in pandas from below snippet:

import pandas as pd

#create dataframe from the college data

data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   })

#display the columns in the dataframe

print(sorted(data))

Output:

['Total Staff', 'college_address', 'college_id', 'college_name']

You can see the sorting is done on columns.

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Method 4 : get columns from pandas dataframe using info() function

This info() method will return the information about column. The information includes:

• column names with associated datatypes and
• count of Not Null values

Syntax:

dataframe.info()

where, dataframe is the input dataframe

 

Example: Lets get get columns from pandas dataframe with all information

import pandas as pd

#create dataframe from the college data

data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":[1200,3422,5644,670]

                   })



#display the columns in the dataframe

print(data.info())

Output: We get columns from pandas dataframe as below

<class 'pandas.core.frame.DataFrame'>

RangeIndex: 4 entries, 0 to 3

Data columns (total 4 columns):

 #   Column           Non-Null Count  Dtype

---  ------           --------------  -----

 0   college_id       4 non-null      object

 1   college_name     4 non-null      object

 2   college_address  4 non-null      object

 3   Total Staff      4 non-null      int64

dtypes: int64(1), object(3)

memory usage: 256.0+ bytes

None

Thus we get other details related to columns as well using info().

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Conclusion

In this article, we first create dataframe in pandas and get columns from pandas dataframe explained in four ways - columns, values, sorted, info.