Python for Finance Retiring the Spreadsheets

For a long time we used spreadsheets to store information. Within a financial market company, several analyzes are carried out every day. From data from different areas and still many professionals in the area do not know. How powerful the Python language is for finance. For each analysis there is a spreadsheet with different data, increasing the consultation time, the chances of making mistakes or business phone numbers list leaving relevant information blank. Fortunately, technology has arrived to facilitate and improve the way we order food. Transport ourselves and even allow us to communicate with someone on the other side of the world in an instant. All this technological convenience has only increased the volume of information and data generated every day.

Python for Finance: A Fantastic Solution

The Python language for finance has been very important and proof of this is the fact that it is one of the most used languages ​​in financial institutions and fintechs and is a great ally of data scientists . Through this tool, you can do everything that spreadsheets do and much, much more! Python is a high-level language created by Guido Van Rossum. Above all, It was made public in 1991 and is known for its simplicity and readability (if you want to know more we have a publication talking about it ). In the financial industry, Python is very useful as it helps to automate critical tasks like collecting data, analyzing and producing useful results. However, It is widely used in quantitative finance – solutions that process and analyze large sets of financial data.

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 To know more

In the investment area, data analysis is fundamental. Therefore, And those who have this ability go far ahead. In this example, we access data from the Yahoo Finance library which is updated daily and contains the history of the main stock exchange indices. Therefore, In this example, we are bringing the history of the Bovespa index. Another relevant information is to try to understand which were the worst and best days of this DV Leads, comparing the output and input values. Below we see the 10 worst days in the history of the iBovespa. Above all, An important part of finance is identifying patterns and relevant information from the company’s database. Therefore, Graphics are essential right now.

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