Critical Point

Welcome to my blog. Here, I post texts about topics of my interest. The posts are dynamic: they might be modified in the future.

2020

Pandas Value Counts

less than 1 minute read

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The value_counts() function in the popular python data science library Pandas is a quick way to count the unique values in a single column otherwise known as a series of data.

Querying the Latest Record

less than 1 minute read

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In this gist, I show how to get the latest record or a user based on a datetime column.

Jupyter Notebook Header

less than 1 minute read

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This gist contains my default settings for a Jupyter notebook as a header.

Datetime Resample

less than 1 minute read

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In this gist, I calculate aggregate the datetime column according to different periods (e.g. day, week, and month)

Cumulative Sum with Pandas

less than 1 minute read

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In this gist, I calculate the cumulative sum of the column no, based on the columns nameand day.

Signing git commits with gpg

19 minute read

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I found this post on how to sign commits with gpg on Medium, and I copied to my blog so I can keep for my records. Please, visit the original source at:

Hypothesis Tests Part 2: Statistical Inference

10 minute read

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In this post, I present an overview of statistical tests. The goal of calculating a test statistic is to decided if the null hypothesis is true. Once value of the test-statistic is obtained, it is compared with a pre-defined critical value. If the test statistic is found to be greater than the critical value, then hypothesis is rejected.

Hypothesis Tests Part 1: Bayesian Inference

4 minute read

Published:

Every quantity that is estimated from data, such as the mean or the variance, is subject to uncertainties of the measurements due to data collection. If a different sample of measurements is collected, value fluctuations will certainly give rise to a different set of measurements, even if the experiments are performed under the same conditions. The use of different data samples to measure the same value results in a sampling distribution that characterize the quantity in consideration. This distribution is used to characterize the “true” value of the quantity in consideration. This blog post is dedicated to present how the collected data is employed to test hypotheses of the quantity being measured.