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Pandas’ query() function allows you to use variables in a query statement, such as dataframe column names, or conditions such as comparison operators. To use a variable, you need to enclose the variable within curly braces ‘{}’, and prefix it with an ‘@’ symbol, such as @variable_name. This will allow you to use the variable within the query statement, such as specifying a particular column for a query or filtering data rows based on a condition.
You can use the following syntax to use the query() function in pandas and reference a variable name:
df.query('team == @team_name')
This particular query searches for rows in a pandas DataFrame where the team column is equal to the value saved in the variable called team_name.
The following example shows how to use this syntax in practice.
Example: How to Use Variable in Pandas Query
Suppose we have the following pandas DataFrame that contains information about various basketball players:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C'], 'position':['G', 'G', 'F', 'G', 'F', 'F', 'F', 'G', 'G', 'F', 'F'], 'points': [22, 25, 24, 39, 34, 20, 18, 17, 20, 19, 22]}) #view DataFrame print(df) team position points 0 A G 22 1 A G 25 2 A F 24 3 B G 39 4 B F 34 5 B F 20 6 B F 18 7 C G 17 8 C G 20 9 C F 19 10 C F 22
Now suppose that we would like to query for the rows where the value in the team column is equal to C.
We can use the following syntax to create a variable called team_name that is equal to ‘C’ and then reference that variable in the query() function:
#specify team name to search for team_name = 'C' #query for rows where team is equal to team_name df.query('team == @team_name') team position points 7 C G 17 8 C G 20 9 C F 19 10 C F 22
Notice that the query() function returns all rows where the value in the team column is equal to C.
Also note that we can reference multiple variables in the query() function if we’d like.
For example, the following code shows how to use the query() function to return all rows where the value in the team column is equal to the value of a variable called team_A or a variable called team_C:
#create two variables team_A = 'A' team_C = 'C' #query for rows where team is equal to either of the two variables df.query('team == @team_A | team == @team_C') team position points 0 A G 22 1 A G 25 2 A F 24 7 C G 17 8 C G 20 9 C F 19 10 C F 22
The query returns all of the rows in the DataFrame where team is equal to the values stored in one of the two variables that we specified.
Note: You can find the complete documentation for the pandas query() function .