Data Analysis Complete Course | Data Analytics Projects | Web-Scraping | Data Visualization

Описание: This is complete course tutorial on Data Analytics by Sumit Shukla (DSML Educator at Scaler)). With this you can master the basics data analytics and it's application. Check out our free masterclasses by industry-leading experts here: https://www.scaler.com/events?utm_sou...

Topics Covered
00:00 - Introduction
00:16 - Panda for Data Analysis
11:28 - Unique & N-Unique Functions
50:21 - Data Visualization in Python
01:46:32 - End-to-End Web Scraping
02:41:15 - Project Case Study

What is Data Analytics?
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. It involves examining raw data with the purpose of drawing conclusions about that information.

What is Data Visualization?
Data Visualization in Python refers to the creation of graphical representations of data using Python libraries such as Matplotlib, Seaborn, Plotly, and others. These libraries provide various functions and methods to generate plots, charts, and graphs that help in understanding and interpreting data.

What are some of the popular Data visualization Libraries?

1. Matplotlib: Matplotlib is a versatile plotting library that allows you to create a wide range of plots, including line plots, scatter plots, bar plots, histograms, and more. It provides fine-grained control over the appearance of plots and is highly customizable.

2. Seaborn: Seaborn is built on top of Matplotlib and provides a higher-level interface for creating attractive statistical graphics. It simplifies the process of creating complex visualizations such as violin plots, box plots, pair plots, and heatmaps.

3. Plotly: Plotly is an interactive plotting library that allows you to create interactive, web-based visualizations. It supports a wide range of chart types, including line plots, scatter plots, bar plots, 3D plots, and more. Plotly also provides APIs for embedding plots in web applications and dashboards.

4. Pandas Visualization: Pandas, a popular data manipulation library in Python, also provides basic plotting functionality through its integration with Matplotlib. It allows you to create simple plots directly from Pandas data structures such as Series and DataFrames.

What is End-to-End Web Scraping?

End-to-end web scraping encompasses the comprehensive process of extracting data from websites, covering all essential steps involved. It begins with identifying the desired data sources, understanding the structure of the target websites, and selecting appropriate tools and technologies for the task at hand. The development of scraping scripts follows, wherein code is written to automate the extraction process, parsing HTML content and extracting relevant data using various techniques. Challenges such as anti-scraping measures may arise, necessitating the implementation of strategies to bypass or mitigate them.

Once data is extracted, it undergoes processing and storage, including cleaning, transformation, and storage in suitable formats. Continuous monitoring and maintenance are crucial to ensure the effectiveness of scraping scripts, along with adherence to legal and ethical considerations surrounding web scraping activities. Through this systematic approach, practitioners can successfully collect data from websites for diverse purposes while respecting the boundaries of legality and ethics.

#scaler #dataanalysis #pyton #webscraping #datavisualization
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