Two nights ago, a small series of analyst friend whispered, finally get the US Treasury website!
This is what the large ones?
Is the current situation, you have to courageous sabotage? Xiao Bian a look of horror.
Do not be afraid, I wrote a Python reptiles, the US Treasury Department website data climb down.
This friend is a bond futures analyst, the daily work requires the latest US Treasury data, but the data on wind 1-2 day delay, only human flesh search the Internet every day. But a lot of data, out of every day miserable.
That finally could not tolerate such a complex boring work, written in Python had a reptile, able to breath data of 200 days to climb down.
So much of the program, even the US financial website can do, you must have spent a lot of time, right?
No, the whole process only 20 lines, my rookie just spent 30 minutes finished!
Small series can not help feeling, in 2019, feeling Python really has become the hard skills of financial analysts, programmers no longer exclusive, and will not be afraid of the future financial analyst Python is a woeful.
In fact, every day and Excel as a data analyst dealing, accountants auditors, the most troublesome thing was too much repetitive work, if before there's a two-month, each data into an Excel file, these data will then be processed manually open, copy, paste and process 40 times, in the end, often have blurred vision to life the suspect.
As artificial intelligence era of beach-goers Python, you can easily solve this problem, just a few lines of code, you can complete Excel take several hours to complete the work. Moreover, the use of powerful Python web crawler processing power can provide a lot of convenience to our research data.
Whether we want to board the official website from debt batch query to retrieve data for a bond SBL stock, or want to obtain data on the Fed's interest rate the US Treasury website, you only need a Python reptile, ten minutes can solve this problem. And before these jobs often require an intern or even a week's time.
And, Python powerful drawing capabilities, allowing data import, analysis, results, drawings can be one-time in the program is completed, you can directly analyze / visualize backtesting results presented.
(Python automatically generated dynamic graph)
Because of this, many domestic financial institutions in the recruitment requirements have been added to Python capabilities. CICC, Galaxy Securities, China Southern Fund, Yinhua Fund has specifically requested proficient with Python data analysis skills when recruiting analyst positions.
We are also the major job sites, excerpts of some of the financial industry skill requirements of the core Hot Jobs:
| Hot Jobs financial sector |
Payroll |
Required Skills |
| Industry analysts |
30w-50w |
Familiar with the industry structure, business model and dynamic data, skilled use of Wind, Excel and so on-line research data analysis tools, the ability to take precedence familiar with Python |
| Macro researcher |
30w-60w |
Strong information gathering capabilities, skilled use of Wind and other financial databases, master basic data analysis, familiar with Python priority |
| Quantify researcher |
Negotiable |
Familiar with Python, skilled use of pandas / numpy / statsmodels and database-related knowledge; for commercial ticket, bond futures, convertible bonds have some knowledge |
| auditor |
20w-40w |
Able to skillfully use Python treatment business audit papers, financial statements priority basis |