NumPy’s ndarray indexing

In NumPy a new kind of array is provided: n-dimensional array or ndarray. It’s usually fixed-sized and accepts items of the same type and size. For example, to define a 2×3 matrix:

When indexing ndarray, it supports “array indexing” other than single element indexing.  (See http://docs.scipy.org/doc/numpy/user/basics.indexing.html)

It is possible to index arrays with other arrays for the purposes of selecting lists of values out of arrays into new arrays. There are two different ways of accomplishing this. One uses one or more arrays of index values. The other involves giving a boolean array of the proper shape to indicate the values to be selected. Index arrays are a very powerful tool that allow one to avoid looping over individual elements in arrays and thus greatly improve performance.

So you basically can do the following:

Besides, when you do equals operation on ndarrays, another ndarray is returned by comparing each element:

Statistics of insurance sold on Taobao.com on Valentine’s Day

On Feb. 14th Taobao launched a campaign to sell insurance products, which promises 7% yearly interest rate. The sales data is public, so I wrote a script to crawl them down and did a brief study on this data. Here’re the results.

On that day (actually sold out in less than two hours in total) more than 40,000 people participated, resulting a total sales of almost one billion CNY (the exact number: 980,270,000 CNY). Two companies participated in this sales campaign: Zhujiang and Tian’an. The sales statistics are:

Zhujiang Tian’an Total
# of Customers 13831 29092 42923
Sales mean (k CNY) 24.922059 21.847003 22.837872
Sales min (k CNY) 1 1 1
Sales 25% (k CNY) 1 2 2
Sales 50% (k CNY) 10 10 10
Sales 75% (k CNY) 20 25 22
Sales max (k CNY) 1000 900 1000
Sales total (k CNY) 344697 635573 980270

The histograms of how many people pay for each amount.

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Zhujiang was extremely popular: in 2 minutes and 56 seconds it reached a sales of 200,212,000 CNY, that’s more than 1 million CNY sales PER SECOND! Indeed Chinese are crazy about online shopping. 😀