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