After importing with pandas read_csv(), dataframes tend to occupy more memory than needed. This is a default behavior in Pandas, in order to ensure all data is read properly. It’s possible to optimize that, because, lighter the dataframe, faster will be the operations you do on them later on. So, let’s first check how much …
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data.table is a package is used for working with tabular data in R. It provides the efficient data.table object which is a much improved version of the default data.frame. It is super fast and has intuitive and terse syntax. If you know R language and haven’t picked up the `data.table` package yet, then this tutorial …
The data.table package in R is super fast when it comes to handling data. It has a syntax that reduces keystrokes while making R code easier to read. These set of exercises are designed to help you to oil your data brain through solving data manipulation exercises. Related post: 101 Python datatable Exercises (pydatatable) 101 …
Python datatable is the newest package for data manipulation and analysis in Python. It carries the spirit of R’s data.table with similar syntax. It is super fast, much faster than pandas and has the ability to work with out-of-memory data. Looking at the performance it is on path to become a must-use package for data …
