How to Drop First Row in Pandas?

In this article, we will discuss how to drop the first row in Pandas Dataframe using Python.

Dataset in use:

Method 1: Using iloc() function

Here this function is used to drop the first row by using row index.

Syntax:

df.iloc[row_start:row_end , column_start:column_end]

where,

• row_start  specifies first row
• row_end specifies last row
• column_start specifies first column
• column_end specifies last column

We can drop the first row by excluding the first row 

Syntax:

data.iloc[1: , :]

Example: Drop the first row

Python3

# import pandas module
import pandas as pd

# create student dataframe with 3 columns
# and 4 rows
data = pd.DataFrame({'id': [1, 2, 3, 4],
                     'name': ['sai', 'navya', 'reema', 'thanuja'],
                     'age': [21, 22, 21, 22]})


# drop first row
data.iloc[1:, :]

Output:

Method 2: Using drop() function

Here we are using the drop() function to remove first row using the index parameter set to 0

Syntax:

data.drop(index=0)

where data is the input dataframe

Example: Drop the first row

Python3

# import pandas module
import pandas as pd

# create student dataframe with 3 columns
# and 4 rows
data = pd.DataFrame({'id': [1, 2, 3, 4],
                     'name': ['sai', 'navya', 'reema', 'thanuja'],
                     'age': [21, 22, 21, 22]})


# drop first row
data.drop(index=0)

Output:

Method 3: Using tail() function

Here tail() is used to remove the last n rows, to remove the first row, we have to use the shape function with -1 index.

Syntax:

data.tail(data.shape[0]-1)

where data is the input dataframe

Example: Drop the first row

Python3

# import pandas module
import pandas as pd

# create student dataframe with 3 columns
# and 4 rows
data = pd.DataFrame({'id': [1, 2, 3, 4],
                     'name': ['sai', 'navya', 'reema', 'thanuja'],
                     'age': [21, 22, 21, 22]})


# drop first row
data.tail(data.shape[0]-1)

Output: