Pandas

Multiple operation on different scenarios of several data sets using Pandas There are 2 project files A. PyCitySchools : Contains (i) PyCitySchools.ipynb - containing code (ii) schools_complete.csv - Data file (iii) schools_complete.csv - Data file

    B. HeroesOfPymoli : Contains 
                        (i) HeroesOfPymoli.ipynb - containing code
                        (ii) urchase_data.csv  - Data File

Trends Observed in PyCitySchools.ipynb :-

1. The Overall Math percentages are lesser than the Overall Reading percentages
2. The performance of The Charter (type) Schools are better than the District (type) Schools.
3. The Schools Spending budget on each student is inversely proportional to the Overall Pass Percentages of the school.
4. Schools with Large Size had Lower Overall Pass Percentages compared to Midium and the Small Sized Schools.

Trends In the Heros of Pymoli

1. We do the analysis to understand the purchasing trend of the people for different kinds of games based on their age, gender,
2. There are about 1163 active players. Majority are male (84%). Number of Female players is smaller (14%).
3. The highest age demographic falls between 20-24 yrs (44.8%)
4. The second group falls between 15-19 yrs (18.60%)
5. The rest of the people fall between 25-29yrs (13.4%)

Some of the Functionalities used are :-

1. Load, merge and read data from .csv files.
2. Groupby , aggregate, len, rename, cut, map, format, sort etc functions used.
3. Analysis like - a. Player Count b. Purchasing Analysis c. Gender Demographics - Clientels were mostly Males d. Purchasing Analysis - Males made more purchases of the games e. Age Demographics - 20-24 yr old people made the largest group of clients - (44.8%)