Air India - Python

Air India is the flag carrier airline of India, based in New Delhi. It is the third-largest airline in India by market share and operates flights to over 100 domestic and international destinations. In this article, we will explore how Python can be used to access and analyze Air India's flight data.

APIs

Air India provides APIs to developers to access its flight data. The APIs provide real-time flight status, schedule information, and other flight-related information. Developers can use these APIs to build applications that can provide useful information to Air India's customers.

Getting Started with API

To use Air India's APIs, developers need an API key. The API key can be obtained by registering on Air India's developer portal. Once registered, developers can use the API key to access the APIs for developing applications.

API Endpoints

Air India provides several APIs that can be used to access flight data. Some of the commonly used APIs are:

• Flight Status API - Provides real-time flight status information.
• Flight Schedule API - Provides flight schedule information.
• Airport API - Provides information about airports.
• Route API - Provides information about routes.

Accessing APIs using Python

Python provides several libraries that can be used to access APIs. One such library is requests. The requests library can be used to make HTTP requests to the APIs and parse the response. Here is an example of how to use requests library to access the Flight Status API:

import requests

api_url = "https://api.airindia.in/apis/FlightStatus"

api_key = "your_api_key"
flight_number = "AI101"

headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + api_key
}

params = {
    "flightNumber": flight_number
}

response = requests.get(api_url, headers=headers, params=params)

if response.ok:
    data = response.json()
    # process data
else:
    print("Error:", response.reason)

Data Analysis

Python provides several libraries that can be used to analyze and visualize the flight data. Some of the commonly used libraries are:

• pandas - Provides data manipulation capabilities.
• matplotlib - Provides data visualization capabilities.
• numpy - Provides numerical computing capabilities.

Analyzing Flight Data

Using pandas, we can load the flight data into a data frame and perform various data manipulation operations on the data frame. Here is an example of how to load flight data using pandas:

import pandas as pd

api_url = "https://api.airindia.in/apis/FlightStatus"

api_key = "your_api_key"
flight_number = "AI101"

headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + api_key
}

params = {
    "flightNumber": flight_number
}

response = requests.get(api_url, headers=headers, params=params)

if response.ok:
    data = response.json()
    df = pd.DataFrame(data)
    # perform data manipulation operations
else:
    print("Error:", response.reason)

Visualizing Flight Data

Using matplotlib, we can create various types of visualizations to analyze the flight data. Here is an example of how to create a bar chart showing the flight count per airport:

import matplotlib.pyplot as plt

api_url = "https://api.airindia.in/apis/FlightStatus"

api_key = "your_api_key"

headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + api_key
}

response = requests.get(api_url, headers=headers)

if response.ok:
    data = response.json()
    df = pd.DataFrame(data)
    airport_counts = df.groupby("airportCode").size()
    airport_counts.plot(kind="bar")
    plt.title("Flight Count per Airport")
    plt.xlabel("Airport Code")
    plt.ylabel("Flight Count")
    plt.show()
else:
    print("Error:", response.reason)

Conclusion

In conclusion, Python can be used to access and analyze Air India's flight data. By using the APIs and various Python libraries, developers can build applications that provide useful information to Air India's customers.