Querying a column from multiple columns based on value in Pandas
In this tutorial, you will learn how to perform lookup operations in Pandas.
Steps to find from one of multiple columns based on value in Pandas
Following are the steps to lookup from one of multiple columns based on the value in Pandas DataFrame.
Import Pandas
We will now import the basic libraries we need to get started.
import pandas as pd
Creating a Pandas DataFrame
We will create a sample DataFrame that we will use to perform the lookup process.
data = {
"Year": ["2000", "2001", "2002", "2003"],
"data": ["a", "b", "c", "d"],
"a": [1, 2, 3, 4],
"b": [5, 6, 7, 8],
"c": [9, 10, 11, 12],
"d": [13, 14, 15, 16],
}
df = pd.DataFrame(data)
In the code above, we create a data
dictionary of lists called . We then pass this dictionary to pd.DataFrame()
the function to create a Pandas DataFrame.
Now let's see how our DataFrame looks like.
print(df)
Output:
Year data a b c d
0 2000 a 1 5 9 13
1 2001 b 2 6 10 14
2 2002 c 3 7 11 15
3 2003 d 4 8 12 16
Use lookup()
the function to find a value from one of multiple columns
We will now data
perform a lookup from one of the multiple columns based on the column value. We will use the function in Pandas lookup()
to perform the required operation.
df["value"] = df.lookup(df.index, df["data"])
In the above code, we have added a value
new column called with lookup()
the lookup value added by the function. In the lookup function, we pass the column name whose index value we want to find in the following columns.
value
We now print the updated DataFrame with the newly added column with the lookup value .
print(df)
Output:
Year data a b c d value
0 2000 a 1 5 9 13 1
1 2001 b 2 6 10 14 6
2 2002 c 3 7 11 15 11
3 2003 d 4 8 12 16 16
We have successfully added a new column with the lookup value in the above output. Hence, we can successfully find the lookup value in Pandas DataFrame by the above method.
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