Overview

• .ipynb file contains code with Markdown cells from Jupyter Notebook.
• Exercises solved by self to answer questions for assignment.
• .html file is .pynb converted to web version for easy viewing
• .csv files contain data on which data analysis was conducted

Datasets and Project Summary

Chicago temperature set

• Cleaning.ipynb - Data cleaning practice
• Histogram-Practice.ipynb - Practicing creating plots
• plots-pandas.ipynb - computing values for plots

Wine Dataset

• appending.ipynb - Appending data from different datasets
• appending_rename.ipynb - Appending, renaming and saving data from different datasets
• assessing_quiz.ipynb - answering Quiz using pandas
• conclusions_groupby.ipynb - using groupby function to analyze quality, ratings and other Questions.
• conclusions_query.ipynb - drawing conclusions to Qs on ratings
• eda_visuals.ipynb - Addressing Qs on wine dataset using different plots
• edavisualspractise_functions.ipynb - Addressing additional Qs using different plots; Here, varying colors are used to differentiate groups
• plottingtypequality.ipynb - Creating plots with matplotlib for ratings
• wine_visualizations.ipynb - Use Matplotlib to create bar charts that visualize the conclusions made with groupby and queries

Cancer Dataset

• assessing.ipynb - inspecting datasets, data types, selecting different ranges
• cleaning_practice.ipynb - practicing data wrangling

Auto Dataset for 2008 and 2018 models

• assessing_case2.ipynb - answering Quiz using pandas
• cleaningcolumnlabels.ipynb - data wrangling
• drawingconclusionsFuel.ipynb - Making inferences and comparisons on fuel efficiency, improvements, classes, etc. and visualizing using histograms and pie charts
• exploring_visuals.ipynb - Making inferences and comparisons using visualizations
• fixdatatypesair_pollution.ipynb - Data Wrangling

• query_filter.ipynb - Data Wrangling

Other Datasets

• matplotlib_example.ipynb - Practicing bar charts
• conclusions_quiz.ipynb - Store Sales Dataset - Analyzing sales figures and periods to determine performance and revenue
• reading_csv.ipynb - Student Scores Data- Reading, writing and inspecting values
• visuals_quiz.ipynb - Powerplant Data - creating plots using matplotlib and answering Quiz questions