Practice for Pandas and Jupyter Notebook
In this project, we analysis the Bike sharing demand data sets from kaggle（https://www.kaggle.com/c/bike-sharing-demand/data） which contains the bike sharing demand for one city in 2011 and 2012.
There are two data sets in this project: "ShareBike.csv" "Weather.csv"
"ShareBike.csv" includes date, season, bike counts.
"Weather.csv" inclueds the weather information.
We use pandas to analysie what factors might affect the demand of sharing bikes.
Data processing includes loading data sets into pandas, clean the data, check the data info, merge different data sets, and data analysis includes data exploitation and visualization.
From the project, we make some interesting observations. We find that the demand of bikes is largely affected by the weather, temperature, while the date, seasons have little impact of the demand.