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 moduleimport pandas as pd# create student dataframe with 3 columns# and 4 rowsdata = pd.DataFrame({'id': [1, 2, 3, 4], 'name': ['sai', 'navya', 'reema', 'thanuja'], 'age': [21, 22, 21, 22]})# drop first rowdata.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 moduleimport pandas as pd# create student dataframe with 3 columns# and 4 rowsdata = pd.DataFrame({'id': [1, 2, 3, 4], 'name': ['sai', 'navya', 'reema', 'thanuja'], 'age': [21, 22, 21, 22]})# drop first rowdata.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 moduleimport pandas as pd# create student dataframe with 3 columns# and 4 rowsdata = pd.DataFrame({'id': [1, 2, 3, 4], 'name': ['sai', 'navya', 'reema', 'thanuja'], 'age': [21, 22, 21, 22]})# drop first rowdata.tail(data.shape[0]-1) |
Output:
