UdacityProject - Investigate-TMDb-Movies-Dataset

Project Overview

In this project, we have to analyze a dataset and then communicate our findings about it. We will use the Python libraries NumPy, pandas, and Matplotlib to make your analysis easier.

What do I need to install?
You will need an installation of Python, plus the following libraries:

• pandas
• NumPy
• Matplotlib
• csv

It will be recommend to installing Anaconda, which comes with all of the necessary packages, as well as IPython notebook.

Why this Project?

In this project, we have to go through the data analysis process and see how everything fits together.
I have also use the Python libraries NumPy, pandas, and Matplotlib, which make writing data analysis code in Python a lot easier!

What I have learn?

After completing the project, I have learned following:

• Know all the steps involved in a typical data analysis process.
• Be comfortable posing questions that can be answered with a given dataset and then answering those questions
• Know how to investigate problems in a dataset and wrangle the data into a format you can use
• Have practice communicating the results of your analysis
• Be able to use vectorized operations in NumPy and pandas to speed up your data analysis code
• Be familiar with pandas' Series and DataFrame objects, which let you access your data more conveniently
• Know how to use Matplotlib to produce plots showing your findings

Project Content

-Table of Contents
-Introduction
-Data Wrangling
-Exploratory Data Analysis
-Conclusions

Important Note: When i was searching, i came across with similar projects which were completed by different persons.
There were 5 different projects which are defined by Udacity Nanodegree Analyst Program.
I made a double check in order to ask different questions and create different codes to seperate my analysis and written codes.
I will suggest Udacity team in order to give us more different projects or giving different project datas for every different course.

Questions that i plan on exploring over the project from this dataset.

1.Best movie which has highest profit
2.Worst movie which has lowest profit
3.Movies which have largest and lowest budgets
4.Movies which have high and low earned revenues
5.Movies which are longest and shortest runtime values
6.Average runtime of all the movies
7.In which year we had most number of profitable movies
8.Successful genres
9.Best 5 Casts & Actors
10.Average profit
11.Average duration of the movies

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