[PYTHON] How strong is your Qiita? Statistics on the number of Contributes seen in the data

Overview

--I tried to analyze the statistical data of Qiita ――I made a quick reference table so that you can understand the power of Qiita --Contribute number, less than 20 people are about 48% of users writing articles ――My Qiita power was about the top 17%

Preface

Recently, I've been less likely to program at home, and how much is my technical ability? I started to think. So, I started thinking, "I'll do my best until the Contribute reaches 1000 in Qiita by the end of this year," in order to improve my technical skills. However, now I have about 157 Contributes. Given that, how difficult is it? Is it realistic? I thought about the feasibility. Therefore, I collected statistical data on the number of Contributes in Qiita and investigated how difficult it was.

Method

You can crawl one by one, but I extracted the desired data from the site called QiitaUserRanking.

https://qiita-user-ranking.herokuapp.com/

The number of Contributes and the data of the number of people were summarized. First of all, scraping is easy.

wget -O - https://qiita-user-ranking.herokuapp.com/chart | grep Bar | grep -o "\[.*\]" | sed "s/\],\[/\n/g" | grep -o "[0-9][0-9]*,[0-9][0-9]*" > data.csv

As the format of data.csv

Number of Contributes,そのNumber of Contributesのユーザーの人数

It is. This data is converted and converted to percentile according to the number of Contributes. Then, write a Python script that outputs according to the Qiita notation.

qiita_stats.py

if __name__=="__main__":
    data = [
        tuple(map(int,l.split(",")))
        for l
        in open("data.csv")
    ]

    all_num = sum(l[1] for l in data)

    for num in [10,20,30,40,50,60,70,80,90,100,200,300,400,500,600,700,800,900,1000,2000,3000,4000,5000]:
        under = sum(l[1] for l in data if l[0] < num)
        print "| %5d | %5d | %5.2f |" % (num,under,(1-float(under)/all_num)*100)
    
    #For ranking yourself
    num = 159
    under = sum(l[1] for l in data if l[0] < num)
    
    print "num %5d : %5d / %5d : %5.2f%%"  % (num,under,all_num,(1-float(under)/all_num)*100)

Here is the output table.

There are 7767 users with less than 10 Contributes. Therefore, users with 10 Contributes are in the top 67.19% of Qiita users. I will take the view. In another example, there are 22063 users with less than 500 Contributes. Therefore, users with 500 Contributes are in the top 6.80%.

Consideration

According to QiitaUserRanking, there are 23,674 people with Contribute of 1 or more. As you can see from the table above, users with 20 Contributes seem to be in the top 52.88%. Therefore, it can be seen that the upper and lower ranks are divided when the number of Contributes is about 20. Currently, my current number of Contributes is 159. As a result of calculating with the script,

num   159 : 19496 / 23674 : 17.65%

The data came out. Therefore, there are 19,496 users with less than 159 Contributes. And ** my ranking seems to be in the top 17.65%. ** **

Impressions

I was aiming

** Users with 1000 Contributes are in the top 3% of Qiita. ** **

I thought it was pretty tough. It's a personal story, but my article has an average Contribute of about 14 per article. Therefore, 72 articles are required to set ** Contribute to 1000. ** Since 2017 is calculated for 7 months, ** Monthly production 10-11 articles. If you write an article about 3 times a week, you will be in time. ** No, this is spicy. If anything, I wanted to write an article with a slightly higher quality or a strong pull, and increase the number of Contributes per article.