Pandas DataFrame query Function
-
DataFrame.query()Method -
Filter Rows of Pandas DataFrame Using the
DataFrame.query()Method -
Filter Rows of Pandas DataFrame With Specified Values for a Column Using the
DataFrame.query()Method -
Filter Rows of Pandas DataFrame Based on Values of Multiple Columns Using the
DataFrame.query()Method
This tutorial explains how we can query rows of Pandas DataFrame in Python using the DataFrame.query() method.
We will use the example to explain how we can query rows of Pandas DataFrame in Python using the DataFrame.query() method.
import pandas as pd
students_df = pd.DataFrame({
'Name': ["Jonathan", "Will", "Michael", "Liva", "Sia", "Alice"],
'Age': [10, 11, 9, 10, 10, 11],
'Group': ["A", "B", "A", "A", "B", "B"],
'GPA': [3.2, 3.5, 4.0, 2.9, 4.0, 3.6]
})
print(students_df)
Output:
Name Age Group GPA
0 Jonathan 10 A 3.2
1 Will 11 B 3.5
2 Michael 9 A 4.0
3 Liva 10 A 2.9
4 Sia 10 B 4.0
5 Alice 11 B 3.6
DataFrame.query() Method
Syntax
DataFrame.query(expr,
inplace=False,
**kwargs)
Parameters
expr |
the query expression used to filter rows from the DataFrame |
inplace |
Boolean. If True, modify the caller DataFrame in-place |
**kwargs |
Keyword Arguments |
Return
It returns a DataFrame formed by the rows which match the expr query.
Filter Rows of Pandas DataFrame Using the DataFrame.query() Method
import pandas as pd
students_df = pd.DataFrame({
'Name': ["Jonathan", "Will", "Michael", "Liva", "Sia", "Alice"],
'Age': [10, 11, 9, 10, 10, 11],
'Group': ["A", "B", "A", "A", "B", "B"],
'GPA': [3.2, 3.5, 4.0, 2.9, 4.0, 3.6]
})
print("The initial DataFrame is:")
print(students_df, "\n")
filtered_df = students_df.query('Group=="A"')
print("The DataFrame of students in Group A:")
print(filtered_df, "\n")
Output:
The initial DataFrame is:
Name Age Group GPA
0 Jonathan 10 A 3.2
1 Will 11 B 3.5
2 Michael 9 A 4.0
3 Liva 10 A 2.9
4 Sia 10 B 4.0
5 Alice 11 B 3.6
The DataFrame of students in Group A:
Name Age Group GPA
0 Jonathan 10 A 3.2
2 Michael 9 A 4.0
3 Liva 10 A 2.9
It filters all the rows having the value of Group column equal to A.
Filter Rows of Pandas DataFrame With Specified Values for a Column Using the DataFrame.query() Method
import pandas as pd
students_df = pd.DataFrame({
'Name': ["Jonathan", "Will", "Michael", "Liva", "Sia", "Alice"],
'Age': [10, 11, 9, 10, 10, 11],
'Group': ["A", "B", "A", "A", "B", "B"],
'GPA': [3.2, 3.5, 4.0, 2.9, 4.0, 3.6]
})
print("The initial DataFrame is:")
print(students_df, "\n")
filtered_df = students_df.query('Age in [10,11]')
print("The DataFrame of students with age greater than 10 years is:")
print(filtered_df, "\n")
Output:
The initial DataFrame is:
Name Age Group GPA
0 Jonathan 10 A 3.2
1 Will 11 B 3.5
2 Michael 9 A 4.0
3 Liva 10 A 2.9
4 Sia 10 B 4.0
5 Alice 11 B 3.6
The DataFrame of students with age greater than 10 years is:
Name Age Group GPA
0 Jonathan 10 A 3.2
1 Will 11 B 3.5
3 Liva 10 A 2.9
4 Sia 10 B 4.0
5 Alice 11 B 3.6
It filters all the rows from the DataFrame students_df having the value of Age column 10 or 11 using the DataFrame.query() method.
Filter Rows of Pandas DataFrame Based on Values of Multiple Columns Using the DataFrame.query() Method
import pandas as pd
students_df = pd.DataFrame({
'Name': ["Jonathan", "Will", "Michael", "Liva", "Sia", "Alice"],
'Age': [10, 11, 9, 10, 10, 11],
'Group': ["A", "B", "A", "A", "B", "B"],
'GPA': [3.2, 3.5, 4.0, 2.9, 4.0, 3.6]
})
print("The initial DataFrame is:")
print(students_df, "\n")
filtered_df = students_df.query('Group =="B" and GPA == 4.0')
print("The DataFrame of students in Group B with GPA 4.0:")
print(filtered_df, "\n")
Output:
The initial DataFrame is:
Name Age Group GPA
0 Jonathan 10 A 3.2
1 Will 11 B 3.5
2 Michael 9 A 4.0
3 Liva 10 A 2.9
4 Sia 10 B 4.0
5 Alice 11 B 3.6
The DataFrame of students in Group B with GPA 4.0:
Name Age Group GPA
4 Sia 10 B 4.0
It selects all the rows in the students_df DataFrame which have value B for the Group column and value 4.0 for the GPA column using the DataFrame.query() method.
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