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Explore and Visualize World Bank CO2 Emission Dataset Using Python
Jupyter Notebook Python
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Exploring and Visualizing of World Bank CO2 Emission Dataset Using Python
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README.md

README.md

Exploring and Visualizing World CO2 Emission Data By Country By Year Using Pandas Dataframe in Python

Abstract Exploratory data analysis is a critical step in understanding data. In this project, we use Pandas dataframe in Python to clean, explore, summarize, and visualize world bank CO2 emission data.

Dataset:

Source : The World Bank Data (downloaded from http://data.worldbank.org/indicator/EN.ATM.CO2E.PC/)

Tools/Platform : ipython notebook (Python 2.7.10, Anaconda 2.3.0(64 bit) (default, May 28 2015, 16:44:52)

Analysis Covered :

  • Getting Started with ipython notebook
  • Get the Data
  • Import the data using Pandas
  • Dataframe characteristics
  • Subsetting the Dataframe
  • Conditional Subsetting
  • Data Cleaning
  • Data Exploration : Exploring data through scatter plots, histograms, bar graphs
  • Creating an interactive searchable widget
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