If you understand the data analysis, you must have heard some of the populist tools such as Excel, Tableau, PowerBI, etc., can become right-hand man of data analysis. But their shortcomings are obvious: tedious operation, reusability poor, single function relatively limited.
How to solve it? --Python
Python has many advantages, if you can really make use of the work, will find work efficiency is greatly improved, the salary increase is only normal thing.
A Python advantages:
"Process control, work efficiency"
For example, Excel for analysis procedure: positioning nulls - deleting null - Modify Data Format - removing outliers - formula - PivotTable - Finishing Data - Insert Chart - adjustment result ......
Every step is cumbersome from a mouse click, if the middle step wrong, a lot of steps need to re-adjust, wasting a lot of time.
But written in Python every step of the process is very convenient, unified language brings unified recording method. When the analysis process needs to modify or reuse, only need to adjust the setting parameters can be good.
If you want to make a variety of good-looking chart, using Python class visualization tools can be, a few lines of code, saving time and effort, but also has interactive features. If you need to modify the code as long as the adjustments, do not waste effort to re-map.
Python Two advantages:
"Tool library rich"
Python high popularity has brought a lot of great God, everything can be described as Python tool library, Python is also widely used to lay a good foundation.
Take for data analysis, visualization with Python will know the basic library matplotlib for example, just his official gallery there are 26 major categories of 527 styles, both in quantity and quality can be rolled on the market most of the same features of the software.
Python Three advantages:
"White friendly and approachable."
Python hear, I think it is programming language, many people will have this concern: I am a non-computer-related professional background, learning the Python programming deviation is not it? I spent a lot of time in learning computer programming, is not the forest for the trees?
On this point we need not worry. Today, businesses need data analysis capabilities, businesses are required Python, and Python syntax is very close to the English, for white learners very friendly, read Python code is like reading the article. Here we look at some word cloud produced using Python code, very easy to understand:
from pyecharts import WordCloud
'''
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'''
name = data_10['关键词'].tolist()
value = data_10['出现频率'].tolist()
wordcloud = WordCloud(width=1300, height=620)
wordcloud.add("", name, value, word_size_range=[20, 100])
wordcloud.render('./参考案例HTML/关键词统计词云图.html')
wordcloud
Import word cloud Kit - Set keyword and the frequency of occurrence - set the size of text and images and other parameters, you can get a word cloud:
you can see, the code in the data analysis work can be done more efficiently, rich and freedom. In fact not only help analyze the code, to better help logical thinking.