In [1]: import numpy as np In [2]: a = np.array([[2,0],[3,0],[3,1],[5,0],[5,1],[5,2]]) In [3]: b = np.zeros((6,3), dtype=”int32″) In [4]: b[a[:,0], a[:,1]] = 10 In [5]: b Out[5]: array([[ 0, 0, 0], [ 0, 0, 0], [10, 0, 0], [10, 10, 0], [ 0, 0, 0], [10, 10, 10]]) Why it works: If you index b … Read more
I would recommend to read this on indexes: http://en.wikipedia.org/wiki/Index_(database). Simply put, a database engine creates a new structure which keeps the indexed column (which corresponds to a property) sorted and a link to the corresponding row for each entry (primary key). This allows for faster searches (since search in ordered lists is faster than in … Read more
There are no such things as associative arrays in Javascript. You can use object literals, which look like associative arrays, but they have unordered properties. Regular Javascript arrays are based on integer indexes, and can’t be associative. For example, with this object: var params = { foo: 1, bar: 0, other: 2 }; You can … Read more
Index order matters when your query conditions only apply to PART of the index. Consider: SELECT * FROM table WHERE first_name=”john” AND last_name=”doe” SELECT * FROM table WHERE first_name=”john” SELECT * FROM table WHERE last_name=”doe” If your index is (first_name, last_name) queries 1 and 2 will use it, query #3 won’t. If your index is … Read more
Use argmax() idxmax() to get the index of the max value. Then you can use loc df.loc[df[‘favcount’].idxmax(), ‘sn’] Edit: argmax() is now deprecated, switching for idxmax()
It depends on how you search. If you search like this: /* Given a value from table1, find all related values from table2 */ SELECT * FROM table1 t1 JOIN table_table tt ON (tt.table_1 = t1.id) JOIN table2 t2 ON (t2.id = tt.table_2) WHERE t1.id = @id then you need: ALTER TABLE table_table ADD CONSTRAINT … Read more
You can do either : > db.collection.ensureIndex({“data.name”: 1,”data.age”:1, “data.job” : 1}) > db.collection.ensureIndex({“data”: 1}) This is discussed in the documentation under indexes-on-embedded-fields and indexes on sub documents The important section of the sub document section is ‘When performing equality matches on subdocuments, field order matters and the subdocuments must match exactly.’ This means that the … Read more
When dealing with indexes, you have to determine what your table is going to be used for. If you are primarily inserting 1000 rows a second and not doing any querying, then a clustered index is a hit to performance. If you are doing 1000 queries a second, then not having an index will lead … Read more
Don’t create Indexes in every column! It will slow things down on insert/delete/update operations. As a simple reminder, you can create an index in columns that are common in WHERE, ORDER BY and GROUP BY clauses. You may consider adding an index in colums that are used to relate other tables (through a JOIN, for … Read more
According to the MySQL 5.1 Reference Manual: If columns are dropped from a table, the columns are also removed from any index of which they are a part. If all columns that make up an index are dropped, the index is dropped as well. If you use CHANGE or MODIFY to shorten a column for … Read more