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Data Structures with Pandas Online Training

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FREE DOWLOAD | Size: 340 MB |  Duration : 1.24Hours  | 15 Video Lessons | 

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ENGLISH | INSTANT DOWNLOAD | ⭐️⭐️⭐️⭐️⭐️ 4.9

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FREE DOWLOAD | Size: 340 MB |  Duration : 1.24Hours  | 15 Video Lessons | 

BRAND: Expert TRAINING | ENGLISH | INSTANT DOWNLOAD | ⭐️⭐️⭐️⭐️⭐️ 4.9

Data Structures with Pandas Online Training

In this intermediate software development skills training, Ben Finkel prepares learners to use the Python packages NumPy and Pandas to start analyzing data.

If you’re learning Python, Pandas and NumPy are among the first packages you’ll stumble across and find essential. NumPy introduces some powerful calculation libraries to your data analysis, including powerful and dimensional arrays. But you need to combine it with Pandas to be really effective. Pandas is a free open source library of data structure and data analysis tools for Python that builds on NumPy and allows you to do some really powerful data manipulation.

After finishing the videos in this Data Structures with Pandas training, you’ll know how to use Python packages like NumPy and Pandas to support and operate on large arrays. In this Python training, you’ll gain an understanding of Pandas data structures and data analysis tools.

For anyone who manages data analysts, this software development training can be used to onboard new data analysts, curated into individual or team training plans, or as a software development reference resource.

Data Structures with Pandas: What You Need to Know

For any data analyst looking to improve their proficiency with scripting languages, this software development course covers topics such as:

  • Navigating data structures with Pandas
  • Understanding NumPy arrays
  • Using Pandas series and DataFrames
  • Importing and processing data with Pandas
  • Processing data with Pandas
  • Using descriptive statistics, iteration, and sorting
  • Understanding covariance and correlations
  • Managing aggregations, grouping and merging

Who Should Take Data Structures with Pandas Training?

This Python training is entry-level programming training, which means it was designed for new software developers, data analysts, IT professionals, or anyone trying to learn Python.

New or aspiring data analysts. If you’re just starting out in data analysis, you’ve probably encountered a number of different tools and resources for extracting meaning from numbers. Not one of them is as widely used or as powerful as Pandas, and this training can show you exactly why. This training in data structures with Pandas will give you expertise in managing large data sources and the many ways to process and navigate them.

Experienced data analysts. Pandas is probably the single most used tool for extracting meaning from huge amounts of data, and if you’re a data analyst, you should be using it. If you’re a data analyst with several years of experience and you deal with large amounts of data, but you’re not proficient in using Pandas to sift through that data and make meaning of it, this training in data structures with Pandas will make your life a lot better and your job much more enjoyable.

 

Data Structures with Pandas

  • 1. Data Structures: Intro to NumPy

    6 mins
  • 2. Data Structures: NumPy Arrays

    7 mins
  • 3. Data Structures: 2D NumPy Arrays

    5 mins
  • 4. Data Structures: Intro to Pandas

    6 mins
  • 5. Data Structures: Pandas Series

    6 mins
  • 6. Data Structures: Pandas DataFrames

    6 mins
  • 7. Data Structures: Pandas Basic Functionality

    5 mins
  • 8. Data Structures: Pandas Import from .csv

    5 mins
  • 9. Data Structures: Importing Real Data with Pandas Lab

    6 mins
  • 10. Using Pandas Data: Descriptive Statistics

    5 mins
  • 11. Using Pandas Data: Iteration

    6 mins
  • 12. Using Pandas Data: Sorting

    4 mins
  • 13. Using Pandas Data: Covariance and Correlation

    3 mins
  • 14. Using Pandas Data: Aggregations

    5 mins
  • 15. Using Pandas Data: Grouping

    4 mins
  • 16. Using Pandas Data: Merging

    5 mins
  • 17. Using Pandas Data: Using Pandas Data Lab

    11 mins

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