🚀 🚀 🚀 SPACE MISSION LAUNCHES 🚀 🚀 🚀

Exploratory Data Analysis

Introduction

In this project, I'm going to explore a dataset with information from varios space mission launches between

Table of contents

1. Objectives
2. Setup
3. Download dataset from Kaggle
   1. Download the mission launches data set
4. Preparation
5. EDA: exploratory data analysis
   1. Who launched the most missions in any given year?
   2. How has the cost of a space mission varied over time?
   3. Which months are the most popular for launches?
   4. Have space missions gotten safer or has the chance of failure remained unchanged?
6. Conclusions

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1. Objectives 🎯 🎯

The main objective is can answer the following questions:

1. Who launched the most missions in any given year?
2. How has the cost of a space mission varied over time?
3. Which months are the most popular for launches?
4. Have space missions gotten safer or has the chance of failure remained unchanged?

2. Setup 📚

I use the following libraries:

• Kaggle for download the dataset from Kaggle
• zipfile for unzip the dataset
• Pandas for managing the data
• Seaborn for visualizing data
• Matplotlib for additional plotting tools
• NumPy for mathematical operations
• SQLAlchemy
• Pandasql

I. Install libraries

!pip install kaggle
!pip install zipfile
!pip install pandas
!pip install seaborn
!pip install matplotlib
!pip install numpy
!pip instal sqlalchemy
!pip install pandasql

3. Download data set 💾

I. In order to download the mission data set i going to use the Kaggle's API. You can download it from this link.

!kaggle datasets download -d sefercanapaydn/mission-launches

II. Unzip dataset

zipfile_name = 'mission-launches.zip'
with zipfile.ZipFile(zipfile_name, 'r') as file:
    file.extractall()

The unzip file is named mission_launches.csv

III. Load data into a dataframe

mission = pd.read_csv('mission_launches.csv')
display(mission.head())
print("Rows x Columns: ", mission.shape)

4. Preparation 🛁 🏃‍♀️

• Analysis of the data types of each column and transformation to the appropriate type.
• Count columns with null values
• Drop columns with unuseful values
• Statistics on numerical columns and string columns
• Count duplicated values and unique values
• Create a new column: Year

5. EDA: exploratory data analysis 🕵️‍♀️ 📈

1. Who launched the most missions in any given year?

Year	Organization	Launches
1976	RVSN USSR	93
1977	RVSN USSR	92
1971	RVSN USSR	90

2. How has the cost of a space mission varied over time?

3. Which months are the most popular for launches?

4. Have space missions gotten safer or has the chance of failure remained unchanged?

6. Conclusion

See attached document: Conclusions_space_missions