Wisdomic Panda

Hold the Vision, Trust the Process.

Beginner's guide to DataFrames in Python using Pandas!

... first choice of data analysts and scientists for data analysis and manipulation that makes importing and analyzing data much easier.

What are DataFrames?

A two-dimensional labeled data structures with columns of potentially different types. So in words of one syllable, you could say that the Pandas DataFrame consists of three main components: the data, the index, and the columns.

Pandas builds on packages like NumPy and matplotlib to give you a single, convenient, place to do most of your data analysis and visualization work.

Why Pandas?

1. Reading data from various sources such as CSV, TXT, XLSX, SQL database, R.
2. Selecting particular rows or columns from dataset.
3. Arranging data in ascending or descending order.
4. Filtering data based on some conditions.
5. Summarizing data by classification variable.
6. Reshape data into wide or long format.
7. Merging and concatenating two datasets.
8. Writing or Exporting data in CSV or Excel format.

🚧 Setting up local environment:

pip install pandas

🚧 Get hands on: Kick-off

• Pandas Cheatsheet - credits: dataquest.io

☕ Ingredients:

• pandas
• numpy
• python3
• Jupyter Notebook
• Anaconda
• Ubuntu 16.4 LTS
• ign.csv Sample dataset

❗ I run on Mac OS/Ubuntu so you might have to slightly modify the code to make it work in your env.

Hey Buddy!

This repository explains the rationale for pandas dataframes in python environment. :warning: I am not much into core data analytics and thus could not cover all features of pandas. But the actual reason behind this kick-off session is that I found this library quite amazing while dealing with Machine Learning Algorithms and NLP tasks. If you are NLP/NLU/NLG or Deep NNs (RNN) enthusiast please have a look at my kick-off-NLP-Natural_Language_Processing-Python for more insights.

Please follow if you find it handy and hit ⭐ to get more kick-off repo updates.

📧 Drop In!! Seriously, it'd be great to discuss Technology.

"The successful warrior is the average man, with laser-like focus" - Bruce Lee.