Leticia Portella's thoughts and learnings

Query if a string is in a list select name, from my.table where name IN ('jon', 'mary') Query within a timestamp select record from my.table where created > timestamp '2019-10-01 00:00' AND created < timestamp '2019-10-01 23:59' Creating

Query if a string is in a list select name, from my.table where name IN ('jon', 'mary') Query within a timestamp select record from my.table where created > timestamp '2019-10-01 00:00' AND created < timestamp '2019-10-01 23:59' Creating

Continuation of My Saga learning Scala - Part 1.

This post is also known as “My saga learning Scala - Part 3“ and is a continuation of Part 1 and Part 2

I decided that I needed to learn a new language and the language I choose was Scala.

This month is my 4 year anniversary of my first job as a developer.

me•di•o•cre: adj.

Being a software engineer at a new company—anywhere—is hard.

Julia is a programming language that I heard a lot for some time now and I knew it deserved my attention.

My participation in technology communities over the last 3 years, lead me to notice that it’s always tricky to show to companies which don’t interact with this technology ecosystem, how beneficial it is for them to get involved.

In this post I’ll tell you about the new JupyterHub authenticator I implemented in the last couple of months, not only technically but also the context in which it was built.

Writing is a good way to evolve your career.

This is the fifth post on my internship on the Outreachy Program with Project Jupyter.

Seaborn Heatmap Simple example with a colormap with light colors on small values and black colors on high values: grouped = df.groupby(['column1', 'column2']).size().unstack() h = sns.heatmap(grouped, cmap='bone_r') Show values of each group: grouped = d…

Seaborn Heatmap Simple example with a colormap with light colors on small values and black colors on high values: grouped = df.groupby(['column1', 'column2']).size().unstack() h = sns.heatmap(grouped, cmap='bone_r') Show values of each group: grouped = d…

This is the forth post on my internship on the Outreachy Program with Project Jupyter.

When you start entering the data science world, things can become really messy.

Pytest minimum example # test_basic.py def test_something(): assert True Parametrize example Creating multiple tests with a single function import pytest def is_even(input): if input % 2 == 0: return True return False @pytest.mark.…

Pytest minimum example # test_basic.py def test_something(): assert True Parametrize example Creating multiple tests with a single function import pytest def is_even(input): if input % 2 == 0: return True return False @pytest.mark.…

Hello there!

In April 2018 I started Udacity’s Nanodegree in Machine Learning Engineer.

AKA magics to plug holes in your dataset

Hello there!

On this post you could have a small idea how SQLAlchemy works.

I’ve been working with Project Jupyter since December of last year and it has been a wonderful experience.

This is the second part of my study on predicting the type of victims an accident can have based on the data from the National Highway Police (Polícia Rodoviária Federal), in Brazil.

Hi :) On November I discovered that I was selected for the Outreachy internship program for the batch of December 2018 to March 2019.

This week, I finished my Nanodegree in Machine Learning Engineer by Udacity.

In today’s development, tests are a fundamental tool for keeping things nice and easy and to keep programmer’s sanity.

I started working with MongoDB for fun and for some side projects in the last year.

I started to study programming logic when I came across problems that required knowledge in Matlab.

KMeans Advantages Good when you have an idea of an ideal number of clusters Can scale well with lots of samples, scale medium with number of clusters Disadvantages Doesn’t handle missing values very well Can’t find clusters that aren’t circular or spheric…

Logistic Regression Advantages Don’t have to worry about features being correlated You can easily update your model to take in new data (unlike Decision Trees or SVM) Disadvantages Deals bad with outliers Must have lots of incomes for each class Presence…

Supervised Models This is a small revision on advantages and disadvantages of each model, based on suggested models of Udacity’s Nanodegree in Machine Learning Engineer.

Sometimes I get just really lost with all available commands and tricks one can make on sklearn.

How to check results of accuracy for each of the classes available on a classification problem?

Starting to contribute to an open-source project is always recommended to someone who is studying to be a programmer.

Undo commits 1 commit: $ git reset HEAD~ 2 commits $ git reset HEAD~~ How to rebase a forked repository On the cloned repository $ git checkout master $ git remote add upstream git@github.com...

Undo commits 1 commit: $ git reset HEAD~ 2 commits $ git reset HEAD~~ How to rebase a forked repository On the cloned repository $ git checkout master $ git remote add upstream git@github.com...

How to list available columns on a DataFrame df.columns.values How to make multiple filters df[(df.column > value1) & (df.column < value2)] How to iterate over a Dataframe for item, row in df.iterrows(): print row() How to count the ocurrences of each

How to change a Series type?

This post could also be called what comes after the tutorials :) In several Django tutorials, we learn how to receive requests and return responses with html pages having several information.

Sometimes I get just really lost with all available commands and tricks one can make on pandas.

This week I ran into a case were I should run several scripts with analysis that could run simultaneously.

The lovely Pyladies-Salvador asked for a text to debut their blog and told me that they would publish it on Women’s Day.

Most of all Django tutorials teach us how to return HTML as response to a request.

One year ago I started my new job as a Backend Python Developer.

As I talked to some people, few new about Django’s Generic Relation and Generic Foreign Key.

Code review is a complicated task and can become overwhelming, specially when you have no idea how to do it.