Python captures financial data, pandas performs data analysis and visualization series (to understand the needs), pythonpandas
Finally, I hope that it is not the preface of the preface. It is equivalent to chatting and chatting. I think a lot of things are coming from the discussion. For example, if you need something, you can only communicate with yourself, only by summing up some things can we better chat with others and talk about them. Today, I want to understand the requirements. In fact, I want to chat with you more. Only by chatting with you can the things behind it make sense and be valuable. In chatting, discovering value in thinking ?) Sometimes you think that something is very important. In fact, it is very important from your own perspective. What you need more is to think about it from the perspective of others and the market, it doesn't matter whether theme is really important. I think there are two types of requirements: What you do on your own initiative and what others want you to do. What others want you to do, you do it very quickly, most people will be able to do it by walking around the kidney. But I took the initiative to do it, I think no one will leave the kidney alone. When you take the initiative to do one thing, that thing will bring value, otherwise it will be nothing more than a waste of time, a waste of life, a waste of good time for sister-in-law, but isn't life a waste? (Conflict)Perception 1:To do data-related work, if you just passively generate some data reports and complete some data reports that do not have your own ideas, do not have any emotional feelings, without attaching your thoughts and thoughts to that pile of boring data, it is a waste of time, a waste of life, and a waste of time. If you work for an enterprise like this, it will always be a human resource, not a talent, and may eventually become a wonderful thing. Therefore, to treat the demand, you can not just take the kidney, don't leave the heart ~ Mining, discovery, curiosity, exploration, and attempt to make mistakes. Taking the initiative to work for yourself, turning the passive into the active habits, not only is it good for your work at hand, it is helpful for the whole person's thinking, this is a permanent task. The demand will come out only after constant thinking. At the beginning of the year, the director asked me to generate a report. The requirement was that at least five new data reports should be generated in a week. What would you do if it was you? After a few weeks, I have produced dozens of data reports. What is the significance of so many data reports? In addition to the amount of data, it seems like it is just a breeze. Oh, I admit that I am leaving the kidney.Sentiment 2:The most important thing about data is not what tools you use. It is your data thinking that makes the data in your hands valuable. I am afraid of a kitchen knife. You use excel to calculate 1 + 1 and python to calculate 1 + 1, both equal to 2. For specific tools, you have to look at your own needs and data scale, and tens of thousands of data, so don't ask what tools to use. You have a good time, cut Vegetables with excel. For example, we have the basic customer information data (user table) on hand, and count the number of customers by region. 2 W records: Just click the excel Pivot table. You said you want to build hadoop to run 2 w Data. why not? 10 million records: it is hard to use excel, and SQL is OK (Select area as 'region', count (area) as 'number' from user group by area) Entries: Use the python pandas Library (User. area. value_counts ()) More than: pandas can be used, but distributed execution is even better. Therefore, it is not the most important tool or tool. The most important thing is how you make the pile of data value for your business. This is the top priority. Of course, it doesn't mean that it will be one way, and you need to keep learning.Sentiment 3:If your job is data analysis, but the leaders do not have the awareness of data, do not change or give up, change or giveup. This is the same as chasing the girl, hot face, cold ass, no. After writing these articles this time, I first understood my needs and decided to (get data-read data-clean and sort data-statistical analysis data-data report output-summary) the knowledge used in this one-stop process is also a full set. Only the work content involved in the daily statistical analysis of small and medium-sized enterprises, half a bucket of sub-water, limited capacity, other levels can be bypassed: Get data: I plan to capture the investment and loan data of XX financial website from the internet for use as the data source. Basically, data in each dimension and format is available for later operations to read data: here, I will divide the obtained data into xls, csv, SQL, and pandas DataFrame data for separate operations to clean and organize data in various data source formats: excel, SQL, both python and javascript are used.
Statistical analysis data: pandas and SQL of python are used. Data report output: I will use django's web development for visualization (html, css, javascript), and the existing report systems, word, pdf, and ppt on hand are all feasible summaries: summarize the methods used and problems encounteredIt is shameful to understand your needs and start your next task. I don't want to agree, I just want to understand. Everyone can make progress together and share discussions and exchange any feelings or problems during their work. Welcome to join me in QQ1749061919 for communication and learning.