indexing
Python: Removing Rows on Count condition
Here you go with filter df.groupby(‘city’).filter(lambda x : len(x)>3) Out[1743]: city 0 NYC 1 NYC 2 NYC 3 NYC Solution two transform sub_df = df[df.groupby(‘city’).city.transform(‘count’)>3].copy() # add copy for future warning when you need to modify the sub df
How to disable index in innodb
Have you tried the following? SET autocommit=0; SET unique_checks=0; SET foreign_key_checks=0; From the MySQL References https://dev.mysql.com/doc/refman/8.0/en/optimizing-innodb-bulk-data-loading.html See Section “Bulk Data Loading Tips“
git: Unable to index file – permission denied
If you are using visual studio or something similar that is generating the mdf file, simply close VS & retry your git command again. This time it should work. To save constantly closing & reopening, you should add references into .gitignore file in the project root. For example, if it is a database causing the … Read more
How does a geospatial index work? [closed]
Depending on the data type and usage pattern, either an R-Tree or variant (R*, R+) or a quadtree or perhaps even a kd-tree.
R-Tree and Quadtree Comparison
Here’s paper which has pretty nice comparison of QuadTrees and R Trees: Quadtree and R-tree Indexes in Oracle Spatial: A Comparison using GIS Data Some differences: Quadtrees require fine-tuning by choosing appropriate tiling level in order to optimize performance. No specific tuning is required for R-Trees. Quadtree can be implemented on top of existing B-tree. … Read more
PostgreSQL UUID type performance
We had a table with about 30k rows that (for a specific unrelated architectural reason) had UUIDs stored in a text field and indexed. I noticed that the query perf was slower than I’d have expected. I created a new UUID column, copied in the text uuid primary key and compared below. 2.652ms vs 0.029ms. … Read more
Speeding up row counting in MySQL
So the question is are there any techniques for speeding up these kinds of queries? Well, not really. A column-based storage engine would probably be faster with those SELECT COUNT(*) queries but it would be less performant for pretty much any other query. Your best bet is to maintain a summary table via triggers. It … Read more
Retrieve name of column from its Index in Pandas
I think you need index columns names by position (python counts from 0, so for fourth column need 3): colname = df.columns[pos] Sample: df = pd.DataFrame({‘A’:[1,2,3], ‘B’:[4,5,6], ‘C’:[7,8,9], ‘D’:[1,3,5], ‘E’:[5,3,6], ‘F’:[7,4,3]}) print (df) A B C D E F 0 1 4 7 1 5 7 1 2 5 8 3 3 4 2 3 … Read more
In Python pandas, start row index from 1 instead of zero without creating additional column
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