Use enumerate when you want both the values and indices in a for loop: for index, item in enumerate(my_list): if item.id == ‘specific_id’: break else: index = -1 Or, as a generator expression: index = next((i for i, item in enumerate(my_list) if item.id == ‘specific_id’), -1)
Just assign directly a new index array: df.index = np.arange(1, len(df) + 1) Example: In [151]: df = pd.DataFrame({‘a’:np.random.randn(5)}) df Out[151]: a 0 0.443638 1 0.037882 2 -0.210275 3 -0.344092 4 0.997045 In [152]: df.index = np.arange(1,len(df)+1) df Out[152]: a 1 0.443638 2 0.037882 3 -0.210275 4 -0.344092 5 0.997045 Or just: df.index = df.index … Read more
Use to_datetime. There is no need for a format string since the parser is able to handle it: In [51]: pd.to_datetime(df[‘I_DATE’]) Out[51]: 0 2012-03-28 14:15:00 1 2012-03-28 14:17:28 2 2012-03-28 14:50:50 Name: I_DATE, dtype: datetime64[ns] To access the date/day/time component use the dt accessor: In [54]: df[‘I_DATE’].dt.date Out[54]: 0 2012-03-28 1 2012-03-28 2 2012-03-28 dtype: … Read more
You could do that in a one-liner using generators: next(i for i,v in enumerate(l) if is_odd(v)) The nice thing about generators is that they only compute up to the requested amount. So requesting the first two indices is (almost) just as easy: y = (i for i,v in enumerate(l) if is_odd(v)) x1 = next(y) x2 … Read more
To rebuild use: ALTER INDEX __NAME_OF_INDEX__ ON __NAME_OF_TABLE__ REBUILD or to reorganize use: ALTER INDEX __NAME_OF_INDEX__ ON __NAME_OF_TABLE__ REORGANIZE Reorganizing should be used at lower (<30%) fragmentations but only rebuilding (which is heavier to the database) cuts the fragmentation down to 0%. For further information see https://msdn.microsoft.com/en-us/library/ms189858.aspx
This: x[:, 1] means “take all indices of x along the first axis, but only index 1 along the second”. This: x[:][1] means “take all indices of x along the first axis (so all of x), then take index 1 along the first axis of the result”. You’re applying the 1 to the wrong axis. … Read more
if you’re using innodb and bulk loading here are a few tips: sort your csv file into the primary key order of the target table : remember innodb uses clustered primary keys so it will load faster if it’s sorted ! typical load data infile i use: truncate <table>; set autocommit = 0; load data … Read more
Short answer: yes. Indexes are dropping on collection drop. You need to recreate an index. You may want to not to drop collection but remove all items in it with db.collection_name.remove({}). It will take more resources but leave your indexes. Actually it will need to delete all index data. That is why it is more … Read more
As @tomharrington said, the solution is in the WWDC 2017 video: Indexing stuff begins at 10:32 and the demo at 16:40. It’s still possible to create and index via Xcode9: First, select your entity, long-click on the + (Add Entity), and select Add Fetch Index. Then, name your index appropriately, the select the property you … Read more