Best Ways to Get Forex Data for Analysis
Tags: forexdata, dataanalysis, realtimedata, pythonsdk
Published: 2023-03-02 08:30:08

Market data is in high demand due to the increased data sets required for financial trading and decision-making. Finding sources of financial market data might be difficult for new users. 

For analytical reasons, users want a reliable historical and streaming currency data source. Reliable data suppliers go to great lengths to serve as many users as possible.


****Delivering the Market Data**
Because of the numerous communication methods, obtaining market data might be tedious for newcomers. Furthermore, different data kinds may necessitate distinct distribution mechanisms. Yet, it does not have to be this difficult. The distribution of their data is becoming more inclusive and accessible thanks to data suppliers.

**Making Use of CSV and Microsoft Excel
**For less advanced users, MS Excel is a terrific tool for acquiring and evaluating Currency data. This can be accomplished by creating third-party Add-ins or by leveraging functions.

Once the data is in Excel, you can analyze it and make decisions. Check out their guide and Excel add-in for importing [historical and real-time data](https://tradermade.com/tutorials/how-to-import-live-forex-cfd-data-in-excel-using-our-add-in/) for Forex, cryptocurrency, and CFD.

They also provide timeseries data, which helps construct technical indicators and chart data as needed. Timeseries data assists you with processing for quality, reviewing, audits, or trading strategy objectives. They also provide CSV downloads for bulk data analysis, making vast data manageable.

**Making Use of WebSockets**
WebSocket is an excellent choice for advanced programmers and analysts that want to evaluate the tick forex in real-time. Its ease of use and quick data analysis allows for real-time decision-making. Users should consider this option if they require a forex data stream for their research.

****Making use of a RESTful API and an SDK**
Financial data can be obtained by programmers via the REST API. There are numerous third-party Python modules available. It is the language of choice for traders and financial experts. The use of APIs has grown. Pandas is one such application. You can use a single command to calculate forex statistics like the daily Range, Correlation, and Standard Deviation.

Read their [Pandas Tutorial](https://tradermade.com/tutorials/fetch-forex-api-with-python-and-pandas/) to discover how to access forex data using Python. Their [Python SDK](https://tradermade.com/tutorials/python-sdk-for-forex-data/) shows you how to obtain real-time currency data (written on top of their API) with just three lines of code. 

Its JSON REST API offers real-time and historical data (OHLC and Tick). They introduce popular programming languages such as Go, JavaScript, and others.


**The Price of Data**
Despite having international corporations as clients, reputable market data vendors strive to ensure access to market data for everyone. As a result, they offer a free option for up to 1000 data requests per month via their API and Excel Add-in.

**Data Reliability**
Data analysis is only as good as the source on which it is based. Therefore data quality is vital. Many solutions are affordable for a purpose. What if the user's decision-making is skewed due to poor data quality? The entire activity will be ineffective or expensive. By combining the data selection options from many vendors, TraderMade gives the best quality in the business.

****Winding-Up**
Obtaining high-quality forex data, in our opinion, is the most crucial component of study and trading. Because it is simple to set up and manage vast amounts of data, MS Excel is a well-accepted solution for non-technical users to collect data. Obtaining forex data from reputable vendors via a Python Pandas module is a fantastic programming learning or beginner's path.