How do I add indexes to MySQL tables?
ALTER TABLE `table` ADD INDEX `product_id_index` (`product_id`) Never compare integer to strings in MySQL. If id is int, remove the quotes.
ALTER TABLE `table` ADD INDEX `product_id_index` (`product_id`) Never compare integer to strings in MySQL. If id is int, remove the quotes.
If the column is not in the WHERE/JOIN/GROUP BY/ORDER BY, but only in the column list in the SELECT clause is where you use INCLUDE. The INCLUDE clause adds the data at the lowest/leaf level, rather than in the index tree. This makes the index smaller because it’s not part of the tree INCLUDE columns … Read more
If you’re using ruby 1.8.7 or 1.9, you can use the fact that iterator methods like each_with_index, when called without a block, return an Enumerator object, which you can call Enumerable methods like map on. So you can do: arr.each_with_index.map { |x,i| [x, i+2] } In 1.8.6 you can do: require ‘enumerator’ arr.enum_for(:each_with_index).map { |x,i| … Read more
An index is used to speed up searching in the database. MySQL have some good documentation on the subject (which is relevant for other SQL servers as well): http://dev.mysql.com/doc/refman/5.0/en/mysql-indexes.html An index can be used to efficiently find all rows matching some column in your query and then walk through only that subset of the table … Read more
DataFrame.reset_index is what you’re looking for. If you don’t want it saved as a column, then do: df = df.reset_index(drop=True) If you don’t want to reassign: df.reset_index(drop=True, inplace=True)
echoing @HYRY, see the new docs in 0.11 http://pandas.pydata.org/pandas-docs/stable/indexing.html Here we have new operators, .iloc to explicity support only integer indexing, and .loc to explicity support only label indexing e.g. imagine this scenario In [1]: df = pd.DataFrame(np.random.rand(5,2),index=range(0,10,2),columns=list(‘AB’)) In [2]: df Out[2]: A B 0 1.068932 -0.794307 2 -0.470056 1.192211 4 -0.284561 0.756029 6 1.037563 … Read more
To see the index for a specific table use SHOW INDEX: SHOW INDEX FROM yourtable; To see indexes for all tables within a specific schema you can use the STATISTICS table from INFORMATION_SCHEMA: SELECT DISTINCT TABLE_NAME, INDEX_NAME FROM INFORMATION_SCHEMA.STATISTICS WHERE TABLE_SCHEMA = ‘your_schema’; Removing the where clause will show you all indexes in all schemas.
Differences KEY or INDEX refers to a normal non-unique index. Non-distinct values for the index are allowed, so the index may contain rows with identical values in all columns of the index. These indexes don’t enforce any restraints on your data so they are used only for access – for quickly reaching certain ranges of … Read more
Use index=False. df.to_csv(‘your.csv’, index=False)
either: df[‘index1’] = df.index or, .reset_index: df = df.reset_index(level=0) so, if you have a multi-index frame with 3 levels of index, like: >>> df val tick tag obs 2016-02-26 C 2 0.0139 2016-02-27 A 2 0.5577 2016-02-28 C 6 0.0303 and you want to convert the 1st (tick) and 3rd (obs) levels in the index … Read more