This content originally appeared on CodeSource.io and was authored by Md Niaz Rahman Khan
In this article, you will learn how to drop the first row in Pandas.
A Pandas DataFrame is nothing but a two-dimensional data structure or two-dimensional array that represents the data in rows and columns. In other words, it is compared to rectangular grids used to store data. It is open-source and potent, fast, and easy to use. Basically, while working with big data we need to analyze, manipulate and update them and the pandas’ library plays a lead role there. Sometimes, we may need to drop the first row in Pandas. There are various ways to perform this action. Such as – using the iloc(), drop(), or tail() function. In this article, we will explore these functions and see how we can perform this action in Pandas DataFrame. First, let’s create a simple Pandas DataFrame in the below section:
import pandas as pd
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John', 'Roy', 'Rohit'],
'Age' : [21, 23, 19, 22, 20],
'Ct_marks1' : [77, 84, 90, 67, 55],
'Ct_marks2' : [58, 74, 77, 87, 75]
})
print(student_df)
# Output:
# Name Age Ct_marks1 Ct_marks2
# 0 Alex 21 77 58
# 1 Deven 23 84 74
# 2 John 19 90 77
# 3 Roy 22 67 87
# 4 Rohit 20 55 75Here, you can see that we have created a simple Pandas DataFrame that represents a few columns. We will perform this action in this Pandas DataFrame.
Example One: drop the first row in Pandas using iloc()
import pandas as pd
import datetime as dt
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John', 'Roy', 'Rohit'],
'Age' : [21, 23, 19, 22, 20],
'Ct_marks1' : [77, 84, 90, 67, 55],
'Ct_marks2' : [58, 74, 77, 87, 75]
})
student_df = student_df.iloc[1:, : ]
print(student_df)
# Output:
# Name Age Ct_marks1 Ct_marks2
# 1 Deven 23 84 74
# 2 John 19 90 77
# 3 Roy 22 67 87
# 4 Rohit 20 55 75Here, you can see that we use the iloc() to drop the first row from the DataFrame. We start printing rows from 1 and it simply ignores the first one.
Example Two: drop the first row in Pandas using drop()
import pandas as pd
import datetime as dt
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John', 'Roy', 'Rohit'],
'Age' : [21, 23, 19, 22, 20],
'Ct_marks1' : [77, 84, 90, 67, 55],
'Ct_marks2' : [58, 74, 77, 87, 75]
})
student_df = student_df.drop(index = 0)
print(student_df)
# Output:
# Name Age Ct_marks1 Ct_marks2
# 1 Deven 23 84 74
# 2 John 19 90 77
# 3 Roy 22 67 87
# 4 Rohit 20 55 75The Drop() function behaves the opposite of the iloc(). Here, we mention the first row and this function simply removes the first one.
Example Three: drop the first row in Pandas using tail()
import pandas as pd
student_df = pd.DataFrame({'Name' : ['Alex', 'Deven', 'John', 'Roy', 'Rohit'],
'Age' : [21, 23, 19, 22, 20],
'Ct_marks1' : [77, 84, 90, 67, 55],
'Ct_marks2' : [58, 74, 77, 87, 75]
})
student_df = student_df.tail(student_df.shape[0]-1)
print(student_df)
# Output:
# Name Age Ct_marks1 Ct_marks2
# 1 Deven 23 84 74
# 2 John 19 90 77
# 3 Roy 22 67 87
# 4 Rohit 20 55 75Like the iloc() and drop() function there is another way of performing this action. The tail() function performs exactly the other two functions. You can see that we use the tail() function along with the shape() to ignore the first row. In the output, you can see that this function removes the first row. These are some useful approaches to perform this action in Pandas.
This content originally appeared on CodeSource.io and was authored by Md Niaz Rahman Khan
Md Niaz Rahman Khan | Sciencx (2022-10-02T09:04:23+00:00) How to drop the first row in Pandas. Retrieved from https://www.scien.cx/2022/10/02/how-to-drop-the-first-row-in-pandas/
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