In this we will study different methods to get rows and column names in a dataframe.<\/p>\n
In this method, we will simply be iterating over all the columns and print the names of each column. Point to remember that dataframe_name. columns give a list of columns.Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(df.columns,'\\n')\r\nprint(\"columns are:\")\r\nfor column in df.columns:\r\n print(column,end=\" \")<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\n<\/span>Index(['Name', 'Age', 'City', 'Marks'], dtype='object') \r\n\r\ncolumns are:\r\nName Age City Marks <\/span><\/span><\/pre>\nHere we see that df. columns give a list of columns and by iterating over this list we can easily get column names.<\/p>\n
\n- \n
Method 2-Using columns.values<\/h3>\n<\/li>\n<\/ul>\n
columns. values return an array of column names. Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"columns are:\")\r\nprint(df.columns.values,'\\n')\r\n<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\ncolumns are:\r\n<\/span>['Name' 'Age' 'City' 'Marks'] \r\n<\/span><\/pre>\n\n- \n
Method 3- using tolist() method<\/h3>\n<\/li>\n<\/ul>\n
Using\u00a0tolist() method with values with given the list of columns. Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"columns are:\")\r\nprint(df.columns.values.tolist(),'\\n')\r\n<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\ncolumns are:\r\n['Name', 'Age', 'City', 'Marks'] <\/span><\/pre>\n\n- \n
Method 4- Access specific column name using index<\/h3>\n<\/li>\n<\/ul>\n
As we know that columns. values give an array of columns and we can access array elements using an index. So in this method, we use this concept. Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"columns at second index:\")\r\nprint(df.columns.values[2],'\\n')<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\ncolumns at second index:\r\nCity \r\n<\/span><\/pre>\nSo these are the methods to get column names.<\/p>\n
Method to get rows name in dataframe<\/h3>\n\n- \n
Method 1-Using index.values<\/h3>\n<\/li>\n<\/ul>\n
As columns., values give a list or array of columns similarly index. values give a list of array of indexes. Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"Rows are:\")\r\nprint(df.index.values,'\\n')\r\n<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\nRows are:\r\n<\/span>[0 1 2 3 4] \r\n<\/span><\/pre>\n\n- \n
Method 2- Get Row name at a specific index<\/h3>\n<\/li>\n<\/ul>\n
As we know that index. values give an array of indexes and we can access array elements using an index. So in this method, we use this concept. Let see this with the help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n('Rahul', 21, 'Delhi' , 97) , \r\n('Aadi', 22, 'Kolkata', 81) , \r\n('Abhay', 24,'Rajasthan' ,76) , \r\n('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"Row at index 2:\")\r\nprint(df.index.values[2],'\\n')<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\nRow at index 2:\r\n2 \r\n<\/span><\/pre>\n\n- \n
Method 3-By iterating over indices<\/h3>\n<\/li>\n<\/ul>\n
As dataframe_names.columns give a list of columns similarly dataframe_name.index gives the list of indexes. Hence we can simply be iterating over all lists of indexes and print rows names. Let see this with help of an example.<\/p>\n
import pandas as pd\r\nimport numpy as np\r\nstudents = [('Raj', 24, 'Mumbai', 95) , \r\n ('Rahul', 21, 'Delhi' , 97) , \r\n ('Aadi', 22, 'Kolkata', 81) , \r\n ('Abhay', 24,'Rajasthan' ,76) , \r\n ('Ajjet', 21, 'Delhi' , 74)] \r\n# Create a DataFrame object \r\ndf = pd.DataFrame( students, columns=['Name', 'Age', 'City', 'Marks']) \r\nprint(\"Original Dataframe\\n\") \r\nprint(df,'\\n')\r\nprint(\"List of indexes:\")\r\nprint(df.index,'\\n')\r\nprint(\"Indexes or rows names are:\")\r\nfor row in df.index:\r\n print(row,end=\" \")\r\n<\/pre>\nOutput<\/p>\n
Original Dataframe\r\n\r\n<\/span> Name Age City Marks\r\n0 Raj 24 Mumbai 95\r\n1 Rahul 21 Delhi 97\r\n2 Aadi 22 Kolkata 81\r\n3 Abhay 24 Rajasthan 76\r\n4 Ajjet 21 Delhi 74 \r\n\r\nList of indexes:\r\n<\/span>RangeIndex(start=0, stop=5, step=1) \r\n\r\nIndexes or rows names are:\r\n0 1 2 3 4 <\/span><\/pre>\nSo these are the methods to get rows and column names in the dataframe using python.<\/p>\n
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Methods to get rows and columns names in dataframe In this we will study different methods to get rows and column names in a dataframe. Methods to get column name in dataframe Method 1: By iterating over columns In this method, we will simply be iterating over all the columns and print the names of …<\/p>\n