In this tutorial, you will learn how to remove the header in Row in Pandas Dataframe with code examples.
Analysis of large datasets can be done with the Pandas Python library. Python libraries matplotlib and NumPy form the foundation of Pandas, which is used for data visualization and mathematical operations.
Many of the methods of matplotlib and NumPy can be accessed through Pandas, which acts as a wrapper for these libraries.
As a result, these data are displayed as rows and columns in Pandas, and the column names are displayed by default in the Pandas Dataframe’s Column section.
Remove Header Row In Pandas
Because the header row in a Pandas dataframe cannot be completely removed. If you do not use the header parameters for the column in the code below, the header will be listed as a number beginning with 0 and ending with the number of columns minus one.
import pandas as pd import numpy as np numpy_data = np.array([[1, 2, 3], [4, 5, 6]]) df = pd.DataFrame(data=numpy_data) print(df)
Output:
0 1
0 1 2
1 3 4As you can see from the code above, I did not use any information to add a header in the column section, and pandas provided the column numbers like 0 and 1.
Though you can certainly hide or remove the header information when you are writing to a CSV file. Or you can use the to_csv() or read_csv() function to remove the header information.
Let us see in the below code example to remove the header row from Pandas dataframe using the to_csv() function while printing.
import pandas as pd import numpy as np numpy_data = np.array([[1, 2, 3], [4, 5, 6]]) df = pd.DataFrame(data=numpy_data) print(df.to_csv(header=None, index= False))
Output:
1,2,3
4,5,6As you can see using the above code I was able to remove the header information from the data that I wanted to print on the screen.
Wrap Up
I hope you have understood the concept of removing header row information from a pandas dataframe. The read_csv() function can be used to achieve the same result as the method that has been listed.
If you know of a better method than the one discussed above, please let me know in the comments section and I will gladly add it here.
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