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Details: Hey, I'm Tomi Mester. This is my data blog, where I give you a sneak peek into online data analysts' best practices. You will find articles and videos about data analysis, AB-testing, research, data science and more…

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SQL for Data Analysis - Tutorial for Beginners - ep1 - Data36

Details: SQL (Structured Query Language) is a must if you want to be a Data Analyst or a Data Scientist.I have worked with many online businesses in the last few years, from 5-person startups up to multinational companies with 5000+ employees and I haven’t seen a single company that didn’t use SQL for data analysis (and for many more things) in some way.

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How to Import Data into SQL Tables Tutorial (3 methods)

Details: A few comments on the .csv import method. I typed \COPY and not just COPY because my SQL user doesn’t have SUPERUSER privileges, so technically I could not use the COPY command (this is an SQL thing). Typing \COPY instead is the simplest workaround — but the best solution would be to give yourself SUPERUSER privileges then use the original COPY command.

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SQL Best Practices for Data Analysts (SQL Tutorial for

Details: Again: the name avg is an automatically generated default name by SQL.But we can change it to anything, using aliases.. E.g. if in the above results we want to see average_depdelay instead of avg, we can achieve it like this:. SELECT AVG(depdelay) AS average_depdelay, origin FROM flight_delays GROUP BY origin;

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Data Analytics Basics (intro for aspiring data professionals)

Details: hi Winnie, yes, the Math BSc. is a good foundation for further data science aspirations. And yes, the next two steps would be SQL + Python and yes, that would leave to an entry/junior level position.

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How to Create a Table in SQL (CREATE TABLE) - Data36

Details: After the CREATE TABLE new_table_name, the column information goes between parentheses.; The different columns have to be separated with commas. I personally recommend using line breaks between columns, and tabs between the column names and the data types.

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What is Data Science? (introduction for beginners)

Details: This is interesting. And I like how you address the different roles within a data team. I think also a great issue is the changing roles of everyone within a data team- with data scientists expected to evolve into more of an analyst role in terms of needing to understand and contribute to business strategy and decision making.

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Python Data Structures (Python & Data Science Basics #2)

Details: Where we did we leave off? Oh, right, we learned about how to use variables in Python.Here is the second essential topic that you have to learn if you are going to use Python as a Data Scientist: Python Data Structures! Note: This is a hands-on tutorial.

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The structure of your Data Team. The flow of the Data in

Details: Smaller companies have smaller data teams (maybe just one person), bigger companies have bigger. The tricky thing is that the several different aspects of a data project need several very different kind of skills.

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Data Science Career Question #1: "Is Data Science For Me

Details: Perfect. A delicious read which I believe accurately sums-up the required profile for such a job. Many people nowadays tend to rush and jump on the Data Science “Hype Train” without taking the time to understand that it is not just a job and not as accessible as advertised online, in institutions and on job postings.

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Python For Loops Explained (Python for Data Science Basics #5)

Details: Remember that I told you last time that Python if statements are similar to how our brain processes conditions in our everyday life? That’s true for for loops too. You go through your shopping list until you’ve collected every item from it. The dealer gives a card for each player until everyone has five.

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Python for Data Science - Tutorial for Beginners #1

Details: There are many more data types, but as a start, knowing these four will good enough and the rest will come along the way. It’s important to know that in Python every variable is overwritable.

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What is Funnel Analysis (with Best Practices and Examples)

Details: Funnel analysis is a powerful analytics method that shows visually the conversion between the most important steps of the user journey. It helps you understand what percent of your users stay with you or churn at a given step.

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Scraping Multiple Pages and URLs with For Loops (Web

Details: This is the second episode of my web scraping tutorial series. In the first episode, I showed you how you can get and clean the data from one single web page.In this one, you’ll learn how to scrape multiple web pages (3,000+ URLs!) automatically, with one 20-line long bash script.. This is going to be fun! Note: This is a hands-on tutorial.

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Python For Loops and If Statements Combined (Data Science

Details: Last time I wrote about Python For Loops and If Statements.Today we will talk about how to combine them. In this article, I’ll show you – through a few practical examples – how to combine a for loop with another for loop and/or with an if statement!

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How to install SQL Workbench for postgreSQL? (6 steps)

Details: In my previous SQL for data analysis tutorial, I briefly mentioned that I prefer SQL Workbench over pgadmin4 for SQL querying.Today I will show you how you can install it too! The setup process is more or less the same on Mac, Windows and Linux, but I’ll highlight the slight differences in my article – and you can always select the appropriate solutions for yourself.

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SQL WHERE clause | Data Analysis in SQL for beginners (ep2)

Details: This is the second episode of my SQL for Data Analysis (for beginners) series, and today I’ll show you every tiny little detail of the SQL WHERE clause.It’s not by accident that I’ve dedicated a whole article to this topic; the WHERE clause is essential if you want to select the right bit of your data from your data table!. In the first half of this article I’ll show you the different

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SQL functions (SUM, AVG, COUNT, etc) & the GROUP BY clause

Details: We are going to modify this query to get 5 interesting numbers: exactly how many flights are in our table (count); the sum of the airtimes (note: practically speaking, airtime is the flight time) of these flights; the average arrival delays and the average departure delays; the maximum distance of any of these flights; the minimum distance of any of these flights

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Sublime Text 3 Intro (+ How to Connect Sublime to a Remote

Details: Multi-select + multi-cursor + multi-edit. Multi-cursor can be used to change the pre-existing parts of your script, too! Let’s say that in your SQL script, you want to change the user_id keyword to email_address.(“Ah, typical, the data infrastructure team changed the column names in our SQL database, again!

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Learning Data Science (4 Untold Truths)

Details: 4 Untold Truths: Accept that learning data science is hard, focus on your skills, consider it an investment and learn the basics first!

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Presentation Tips for Data Professionals

Details: (The links are affiliate links, but I added the non-affiliate versions of them, too.) Presentation ZEN: If you read only one book on presenting well, it should be this one. It’s a good read with nice stories — and at the same time jam-packed with value.

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Pandas Tutorial 2: Aggregation and Grouping

Details: Let’s continue with the pandas tutorial series. This is the second episode, where I’ll introduce aggregation (such as min, max, sum, count, etc.) and grouping.

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How to Run a Python Script? (Step by Step Tutorial, with

Details: In this tutorial, you’ll learn how to run a Python script. And it’s quite essential. When working on data science projects, you’ll write Python code all the time… You know that already. But when you start to automate these tasks (either it’s data cleaning, data loading, analytics, machine learning algorithms or anything else) you’ll rely heavily on scripting.

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SQL current date (and time, month, year, etc.) in postgreSQL

Details: Working with current dates and times in data science projects is quite common. In this episode of my SQL tutorial series I’ll show you the best functions that return the actual time and date — or part of them. I won’t just show you the SQL current date function, but many alternatives, so you can pick the one that fits your needs the best. Do you need the current:

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Predictive Analytics 101 - the basics explained for non

Details: Last week I promised to continue with the second Part of Predictive Analytics 101. If you haven’t read Part 1, please do that here: Predictive Analytics 101 Part 1. In Part 1 I introduced the main concept of Predictive Analytics and also wrote about how predictions are useful for all online businesses.

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Data Science Projects for Boosting Your Resume (Best

Details: We all know the old catch-22 — you need a job to get job experience and job experience to get a job. Luckily, that’s not entirely true in data science. You can use personal data science projects to demonstrate your skills to prospective employers — especially for landing your first data science job.

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Pandas Tutorial 3: Important Data Formatting Methods

Details: The theory is exactly the same for pandas merge. When you do an INNER JOIN (that’s the default both in SQL and pandas), you merge only those values that are found in both tables.On the other hand, when you do the OUTER JOIN, it merges all values, even if you can find some of them in only one of the tables.

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Statistical Averages - Mean, Median and Mode - Data36

Details: As I have mentioned several times, Data Science has 3 important pillars: Coding, Statistics and Business.To succeed, you have to be well-versed in all three. In this new series, I want to help you to learn the most important parts of Statistics.This is the first step – and in this episode we are going to get to know the most basic statistical concept: statistical averages.

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Expected Value (Formula, Explanation, Everyday Usage and a

Details: The calculation goes: (0.5 * $0) + (0.4 * $2) + (0.1 * $10) = $1.80. So the expected value of this game is: $1.80. In other words if you played it long enough, let’s say for 10,000 rounds, you’d end up with something pretty close to $18,000 (which is 10,000 * $1.80, you know).. Obviously, if you played only one round, you’d get $10, $2 or $0… and not $1.80.

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My Computer Setup for Data Science (Apps, Programs, Software)

Details: I made a list of the tools, apps and programs that I installed to my new laptop, so I can share my exact data science computer setup with you.

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Variables, if statements and while loops in bash (Data

Details: In this article I will show you 3 data coding concepts: variables, if-then-else statements and while loops. It will be useful for bash, Python & R too.

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SQL for Data Analysis - Tutorial - ep6 - Some Advanced SQL

Details: See? The trick is that the CASE WHEN statement is creating a new column at the end of the table.. To be honest I don’t use the SQL CASE statement too often during my daily job… but sometimes it’s very handy when I have to do some quick and dirty data cleaning/transformation, turn a continuous value into a categorical value (like we did in the above example), and so on…

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Pandas tutorial 5: Scatter plot with pandas and matplotlib

Details: Scatter plots are frequently used in data science and machine learning projects. In this pandas tutorial, I’ll show you two simple methods to plot one. Both solutions will be equally useful and quick:

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Linear Regression in Python using numpy + polyfit (with

Details: If you put all the x–y value pairs on a graph, you’ll get a straight line:. The relationship between x and y is linear.. Using the equation of this specific line (y = 2 * x + 5), if you change x by 1, y will always change by 2.And it doesn’t matter what a and b values you use, your graph will always show the same characteristics: it will always be a straight line, only its position and

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How to Create UTM Codes and Track Your URLs

Details: Using UTM codes (campaign, source, medium, term, content) is the simplest and most accurate way to track your campaigns' performance in Google Analytics.

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How to Plot a Histogram in Python Using Pandas (Tutorial)

Details: Hey, I'm Tomi Mester. This is my data blog, where I give you a sneak peek into online data analysts' best practices. You will find articles and videos about data analysis, AB-testing, research, data science and more…

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SQL TRUNCATE TABLE and DROP TABLE (tutorial)

Details: In this episode of the SQL tutorial series you’ll learn two simple but important commands that you’ll use frequently when working in SQL: TRUNCATE TABLE and DROP TABLE. TRUNCATE TABLE is to delete all the data from an SQL table.; DROP TABLE is to delete the table itself.; Let’s see how they work in practice!

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Learn Data Analytics in Bash - from scratch (7 articles)

Details: In the last few months I have worked really hard to put together a introductory course in data coding for those who are new to Data Science. I’ve selected bash (aka the command line) as the first data language to show you, because I find it easy to interpret – even for first timers.

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What's the best computer/laptop for a data scientist?

Details: What's the best computer or laptop for a data scientist? In this article, I'll answer it in detail and I'll add specific recommendations, too.

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Learn SQL for Data Analysis from Scratch (10+1 articles)

Details: Hey, I'm Tomi Mester. This is my data blog, where I give you a sneak peek into online data analysts' best practices. You will find articles and videos about data analysis, AB-testing, research, data science and more…

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Why Become a Data Scientist? (7+1 Selfish Reasons)

Details: Conclusion. I hope my 7+1 reasons helped you to see the bright side of being a data scientist. Next time, I’ll write about how to decide if it is the best fit for you or not.

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Statistical Significance in A/B testing (Calculation, p

Details: STEP 3) Then we will simulate chance. (Sounds cool, right?) The way we do that is that we take the 10 “A” and the 10 “B” values that we removed in the previous step and we re-assign them randomly to our users.. This is a key step: when we randomly assign A and B values, there is a chance that something extreme occurs.

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Customer Retention Analysis - Calculate Retention, Use

Details: A good retention strategy is easier to build on proper data That's why you need customer retention analysis done right in your online business.

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Python Import Statement --- plus: Built-in Modules for

Details: These are divided into three groups: The modules of the Python Standard Library: You can get these really easily because they come with Python3 by default. You simply have to type import and the name of the module – and from that point on you can use the given module in your code. In this article, I’ll show you exactly how to do that in detail.

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Page 4 – Data36

Details: Hey, I'm Tomi Mester. This is my data blog, where I give you a sneak peek into online data analysts' best practices. You will find articles and videos about data analysis, AB-testing, research, data science and more…

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How to connect Google Data Studio to PostgreSQL (6 steps)

Details: hey Eran, if you did everything like it was described (and I assume you did, since PgAdmin is working), then it might be a firewall issue. Try to run SQL Workbench as administrator (if you are on windows), pause your firewall programs and/or whitelist SQL Workbench and your server’s IP and it should work!

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Thank you for registering! - Data36

Details: You got access to the Data36 Inner Circle. I’ll send you the welcome email in ~30 seconds. There you will find more info and most importantly: the link to your free learning materials.. And this is just the beginning. So stay tuned! … Just one more thing:

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Statistical Bias Types explained (with examples) - part1

Details: Observer bias happens when the researcher subconsciously projects his/her expectations onto the research. It can come in many forms, such as (unintentionally) influencing participants (during interviews and surveys) or doing some serious cherry picking (focusing on the statistics that support our hypothesis rather than those that don’t.). Everyday example of observer bias:

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Python 2 vs Python 3 - Data36

Details: “Should I learn Python 2 or Python 3?” For everyone who has just started to learn Python for Data Science, this is an important initial question to answer.There are many ongoing discussions on the topic and you might have found it hard to get a straightforward answer.

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Statistical Variability (Standard Deviation, Percentiles

Details: In my previous article about statistical averages, we discussed how you can describe your dataset with a few central values (mean, median and mode).That’s well and good… But there is a problem with statistical averages: they don’t tell you too much about the statistical variability (or in other words the spread or dispersion) of your data.. E.g. if you compare these two datasets:

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