API Data Analysis Using Pandas

Introduction

In today's data-driven world, organizations increasingly rely on APIs to retrieve and analyze data from various sources.

Setting Up Environment

Installing Necessary Libraries

To work with API data, we primarily need the following Python libraries:

• Pandas: For data manipulation and analysis.
• Requests: To make API calls.
• Matplotlib & Seaborn: For visualization.

pip install pandas requests matplotlib seaborn

Introduction to Jupyter Notebook

pip install jupyter
jupyter notebook

Obtaining API Data

Finding Suitable APIs for Analysis

Commonly used APIs include OpenWeather, CoinGecko, Alpha Vantage, and COVID-19 API.

Using the Requests Library

import requests
API_KEY = 'your_api_key'
url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=TSLA&apikey={API_KEY}'
response = requests.get(url)
data = response.json()
print(data)

Data Preprocessing

Converting API Data into a Pandas DataFrame

import pandas as pd
df = pd.DataFrame.from_dict(data['Time Series (Daily)'], orient='index')
df.columns = ['Open', 'High', 'Low', 'Close', 'Volume']
df = df.astype(float)
df.index = pd.to_datetime(df.index)

Data Exploration and Analysis

Generating Descriptive Statistics

print(df.describe())

Visualizing Data

import matplotlib.pyplot as plt
plt.plot(df.index, df['Close'])
plt.title('Stock Closing Prices Over Time')
plt.show()

Advanced Data Analysis Techniques

Grouping and Aggregating Data

monthly_avg = df.resample('M').mean()

Applying Filters

high_volatility = df[df['High'] - df['Low'] > 10]

Case Study: Analyzing Stock Market Data

Obtaining Stock Market Data

url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=TSLA&apikey={API_KEY}'
response = requests.get(url)
data = response.json()
df = pd.DataFrame.from_dict(data['Time Series (Daily)'], orient='index')

Conclusion

Summary

API data analysis involves retrieving, cleaning, and analyzing data efficiently.

Future Applications

Potential applications include finance, healthcare, e-commerce, and social media analytics.

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