How to Access a Row in a DataFrame
You can use the loc and iloc functions to access rows in a Pandas DataFrame. Let’s see how.
In our DataFrame examples, we’ve been using a Grades.CSV file that contains information about students and their grades for each lecture they’ve taken:
Now let’s imagine we needed the information for Benjamin’s Mathematics lecture. We could simply access it using the iloc function as follows:
Benjamin_Math = Report_Card.iloc
The above function simply returns the information in row 0. This is useful, but since the data is labeled, we can also use the loc function:
Benjamin_Math = Report_Card.loc[(Report_Card["Name"] =="Benjamin Duran") & (Report_Card["Lectures"] == "Mathematics")]
In this case, we are using simple logic to index our DataFrame:
- First, we check for all rows where the Name column is Benjamin Duran
- Within that result, we then look for all rows where the Lectures column is Mathematics.
This will return us a DataFrame matching the result of the iloc example above.
And if we wanted to access Benjamin’s Mathematics grade and store it in a variable, we could simply do the following:
grade = Benjamin_Math["Grades"]
Since we only have one row of information, we can simply index the Grades column, which will return us the integer value of the grade.
Now that you know how to access a row in a DataFrame using Python’s Pandas library, let’s move on to other things you can do with Pandas:
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