How to Cultivate Analytics at Work by Transforming Data Instantly, With no Lag A deep understanding on how to use the Transform and Aggregate methods of Pandas Group By object, in supporting various critical operational decisions Continue Reading →
How to Join Arrays and Predict Problem Location, Numpy Outlier Cartesian product solves brilliantly when applied in the right context of the problems. Explained in detail with an industrial use case and code examples. Continue Reading →
Numpy ReduceAt, Simple Method to Isolate Problem with Data Slices Core technique behind moving averages and continuous calculations. Explained in detail with an industrial use case and code examples. Continue Reading →
How to Detect More Data Patterns with Numpy Reduce The root technique of many collaborative filtering algorithms. Explained in detail with an industrial use case and code examples. Continue Reading →
Better Data Filter for Custom Logic, Numpy At Understanding the direct applications of the most brilliant Python library Numpy. Index based filtering of an array is a proven good feature in defining custom logics. Explained in detail with an industrial use case and code examples. Continue Reading →
An Easy Way to Detect Data Abnormalities, Numpy Accumulate A proven technique for a faster and accurate data comparisons. Explained in detail with an industrial use case and code examples. Continue Reading →
Resampler Unique Method to Determine Stability In Time Series Data A simple yet powerful technique to detect stability trend. Explained in detail with a retail use case and code examples. Continue Reading →
A Full Method To Describe Time Series Windows, Resampler OHLC Smart way of presenting time windows for subjective decisions. Explained in detail with a retail use case and code examples. Continue Reading →
A Simple Method to Estimate Missing Time Series, Resampler Interpolate A regression based scientific method in exploratory data analysis. Explained in detail with a retail use case and code examples. Continue Reading →
An Easy Method to Handle Missing Data, Resampler Backfill A flexible and scientific method in exploratory data analysis. Explained in detail with a retail use case and code examples. Continue Reading →
