This project is a groupwork with 2 members (Suraj and me) for the cleaning, tidying, and analyzing with Pandasing and cleaning of Data.

In this project, we will be working on three different raw data and analyzing/visualizing to show as mush as information we can obtain.

For the analysis_dataset jupyter notebook file: it analyzes the dataset related with the deposition of atmospheric pollutants.The source of data is UK Environmental Change Network. This contains the eleven different site's ongauge measurement of composition of different chemical for the sampling day (Date in which the sample is collected.)

The second file, Tidy_dataset is work of analyzing of a dataset contains historical snapshots of the IDA Statement of Credits and Grants including the latest available snapshot. The World Bank complies with all sanctions applicable to World Bank transactions.

The last work is in Tidy_and_analysis jupyter notebook file. this work is based on the dataset about bankruptcy prediction of Polish companies. The data was collected from Emerging Markets Information Service (EMIS, [Web Link]), which is a database containing information on emerging markets around the world. The bankrupt companies were analyzed in the period 2000-2012, while the still operating companies were evaluated from 2007 to 2013. Basing on the collected data, five classification cases were distinguished, that depends on the forecasting period.

In these work, several method of data cleaning and visualization will be used such as:

• Using heatmap to see missing values or correlation.
• Using plotly to visualize the information obtains from analyzing
• Folium map
• etc...