Project Description
Financial markets are an important part of the global economy and are closely followed by investors, economists and analysts. In this project, we will evaluate stock performances, the effects of economic indicators and company information by analyzing various financial market data. Our goal is to identify market trends, support investment decisions and understand the impact of economic indicators on stocks. This analysis will provide valuable insights for investors and financial analysts.
Project Usage Areas
This project has several uses for financial analysts, investors and economists:
Analysis of Market Trends: Supporting long-term investment decisions by examining changes in stock prices over time.
Effects of Economic Indicators: Analyzing the effects of economic indicators (GDP, unemployment rate, inflation, interest rates) on stock performances.
Evaluation of Company Performance: Making sector-based comparisons by examining company information and financial performances.
Impact of News: Determining the impact of news about companies on stock prices.
Investment Strategies: Developing effective investment strategies and portfolio management using data analysis.
Dataset Description
The data set to be used in this project includes financial market data. The dataset consists of four main files in total:
Shares (stocks)
Date: Date
Company: Company name
Open: Opening price
Close: Closing price
High: The highest price during the day
Low: Lowest price during the day
Volume: Transaction volume
Economic Indicators (economic_indicators)
Date: Date
GDP: Gross Domestic Product
UnemploymentRate: Unemployment Rate
InflationRate: Inflation Rate
InterestRate: Interest Rate
Company Information (company_info)
Company: Company name
Sector: Sector
MarketCap: Market Cap
Employees: Number of Employees
Country: Country
News
Date: Date
Company: Company name
Title: News title
Content: News content
There are various dirty data problems in this dataset, such as missing data, outlier data, and wrong data type. This is an ideal data set to experience data cleaning and processing processes commonly encountered in real life.
Student Benefits
This project provides many benefits for students:
Data Manipulation: Students develop skills in examining, cleaning, and analyzing data sets.
Using Pandas: They learn to use the data processing and analysis methods of the Pandas library effectively.
Data Cleaning: They gain skills in cleaning missing data, outliers and incorrect data types.
Business Intelligence: By analyzing data sets, they improve their ability to evaluate financial market trends and make strategic investment decisions.
Reporting: Provides skills to effectively report and present analysis results.
Real Life Applications: Provides practical information about data problems and analysis processes encountered in real life.
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