30 Dec Indexing in Pandas
In this lesson, we will learn how Indexing works in Pandas. We can easily index and select data in Pandas. Before moving further, we’ve prepared a video tutorial to understand indexing in Pandas:
Let’s say we have the following CSV file Students.csv:
Indexing
Indexing means selecting specific rows and columns of data from DataFrame. A DataFrame includes columns, index, and data. Let us see some examples:
- Indexing in Pandas using the indexing operator
- Indexing in Pandas using loc[]
- Indexing in Pandas using iloc[]
Indexing in Pandas using the indexing operator
We can directly use the [] i.e. the indexing operator in Pandas to retrieve records. Let us see an example:
import pandas as pd
# Input CSV file
# Loading CSV in the DataFrame
df = pd.read_csv('Students.csv',index_col ="Student")
# Display the CSV file records
print("Our DataFrame =\n", df)
# Use the indexing operator
res = df["Marks"]
# Retrieving marks of students
print("\n",res)
Output
Our DataFrame = Student Rank Marks Amit 1 95 Virat 2 90 David 3 80 Will 4 75 Steve 5 65 Student Amit 95 Virat 90 David 80 Will 75 Steve 65
Indexing in Pandas using loc[]
To retrieve a single row in Pandas, use the loc[] in Pandas. Let us see an example:
import pandas as pd
# Input CSV file
# Loading CSV in the DataFrame
df = pd.read_csv('Students.csv',index_col ="Student")
# Display the CSV file records
print("Our DataFrame =\n", df)
# Retrieving a single row with Name Amit
print("\n",df.loc["Amit"])
Output
Our DataFrame Student Rank Marks Amit 1 95 Virat 2 90 David 3 80 Will 4 75 Steve 5 65 Rank 1 Marks 95 Student: Amit, dtype:object
Indexing in Pandas using iloc[]
To retrieve the rows and columns by position, use the iloc[] in Pandas. Let us see an example:
import pandas as pd
# Input CSV file
# Loading CSV in the DataFrame
df = pd.read_csv('Students.csv',index_col ="Student")
# Display the CSV file records
print("Our DataFrame =\n",df)
# Retrieving row 3 records
res = df.iloc[2]
print("\n",res)
Output
Our DataFrame = Student Rank Marks Amit 1 95 Virat 2 90 David 3 80 Will 4 75 Steve 5 65 Student David Rank 3 Marks 80
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