While analyzing the real datasets which are often very huge in size, we might need to get the rows or index names in order to perform some certain operations.
Let’s discuss how to get row names in Pandas dataframe.
First, let’s create a simple dataframe with nba.csv
Python3
import pandas as pd
data_top = data.head( 10 )
data_top
|

Now let’s try to get the row name from above dataset.
Method #1: Simply iterate over indices
Python3
import pandas as pd
data = pd.read_csv( "nba.csv" )
data_top = data.head()
for row in data_top.index:
print (row, end = " " )
|
Output:
0 1 2 3 4 5 6 7 8 9
Method #2: Using rows with dataframe object
Python3
import pandas as pd
data = pd.read_csv( "nba.csv" )
data_top = data.head()
list (data_top.index)
|
Output:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
Method #3: index.values
method returns an array of index.
Python3
import pandas as pd
data = pd.read_csv( "nba.csv" )
data_top = data.head()
list (data_top.index.values)
|
Output:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
Method #4: Using tolist()
method with values with given the list of index.
Python3
import pandas as pd
data = pd.read_csv( "nba.csv" )
data_top = data.head()
list (data_top.index.values.tolist())
|
Output:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
Method #5: Count number of rows in dataframe
Since we have loaded only 10 top rows of dataframe using head()
method, let’s verify total number of rows first.
Python3
for row in data.index:
print (row, end = " " )
|
Output:

Now, let’s print the total count of index.
Python3
import pandas as pd
data = pd.read_csv( "nba.csv" )
row_count = 0
for col in data.index:
row_count + = 1
print (row_count)
|
Output:
458