Python: Working with Lists

Making a list in Python is simple: x = [1,2,3,4]

Now let us see how we can work with them.

Index

First thing to understand is that a list is indexed. Each item in the list is given a number that tells you its position in the list.

It is important to note that Python is a 0 index language. This means indexes begin at 0 not 1. So the first item in the list, is found by calling: x[0]

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Note that x[4] returns an error. Since there are 4 items in the list, the indexes go 0,1,2,3. Index 4 is out of range.

Another interesting point to understand about indexes is that you can use a negative index. x[-2]  returns Duck

Try your code in our online Python console: 

Index Range

Use a “:” to return a range of items from a list: x[start:end]. If you leave out the start or end number, the index starts or ends at the start or end of the list

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Update Values in a List

If you want to change a value in a list, just assign it a new value like you would with a regular variable.

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Append()

If you want to add an item to then end of a list, you can use the Append() function

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Del

To delete a item from a list, use the Del command.

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Remove()

Remove works like Del, except instead of using index values, Remove() uses the values stored in the list.

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Try your code in our online Python console: 

Pop() and Insert()

Pop() simply returns the last item from a list

Insert() lets you add a item to a list, but it also lets you choose what position in the list to add it.

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Len()

Len() returns a count of the number of items in a list.

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Try your code in our online Python console: 

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Last Lesson: Python Lists and Dictionaries

Next Lesson: Working with Dictionaries

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Python: Intro to Graphs

Visualizations are big part of analytics. You will need to produce visually engaging graphics for presentations, reports, and dashboards. You will also make graphs for your own use in data discovery and analysis. As bonus, unlike data cleaning, data viz can be pretty fun.

Matplotlab and Pyplot

Matplotlab is a module you can import into Python that will help you to build some basic graphs and charts. Pyplot is part of Matplotlab and the part we will be using in the following example.

**If you are using the Anaconda Python distribution, Matplotlab is already installed. If not, you may need to download it from another source.

Line Graph

Syntax

  • %matplotlib inline – this code allows you to view your graphs inside jupyter notebooks
  • from matplotlib import pyplot as plt – here we import pyplot from matplotlib into our program (note, we only want pyplot not all the functions in matplotlib).Adding “as plt” gives us a shorter alias to work with
  • age and height lines – fill our lists with age and height information for an individual
  • plt.plot(age, height, color = ‘blue’) – here we tell Python to plot age against height and to color our line blue
  • plt.show() – prints out our graph

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Bar Chart

For this example, we will make a bar charting showing ages of 4 people.

Syntax

  • You should understand the first few lines from the first example
  • count_names = [i for i,_ in enumerate(name)]  – since the name list is a list of strings, we cannot really graph that onto a chart. We need a way to convert these strings into numbers.

Wait? What does for i,_ mean? Let’s jump to the next code sample

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While you don’t see it when making the list, a Python list is technically a list of tuples (index number, element). So if instead of i,_ we asked for both elements in the tuple, (i,j) we would get the following.

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So by iterating by for i,_ we only return the first element in the tuple (the index)

** notice we are using a list comprehension. If you are unfamiliar with list comprehensions, check out my earlier post: Python: List Comprehension

Let’s clean up our bar chart a little now.

  • plt.ylabel(‘Age’) – label the y-axis Age
  • plt.title(‘Age of People’) – give the graph a title
  • plt.xticks([i+0.5 for i,_ in enumerate(name)], name) – this label function is using a list comprehension to first chose the position on the X-axis, and name provides the person’s name for the label.

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R: Intro to Statistics – Central Tendency

Central Tendency

One of the primary purposes of statistics is to find a way to summarize data. To do so, we often look for numbers known as collectively as measurements of central tendency (mean, median,  mode).

Look at the list below. This is a list of weekly gas expenditures for two vehicles. Can you tell me if one is better than the other, or are they both about the same?

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How about if I show you this?

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Using the average, you can clearly see car2 is more cost efficient. At approx $21 a week, that is a savings of $630 over the course of the 30 weeks in the chart. That is a big difference, and one that is easy to see. We can see this using one of the 3 main measures of central tendency – the arithmetic mean – popularly called the average.

Mean

The mean – more accurately the arithmetic mean – is calculated by adding up the elements  in a list and dividing by the number of elements in the list.

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In R, finding a mean is simple. Just put the values you want to average into a vector (**note to make a vector in R: var  <-c(x,y,z)) We then put the vector through the function mean()

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Median

The median means, simply enough, the middle of an ordered list. This is also easy to find using R. As you can see, you do not even need to sort the list numerically first. Just feed the vector to the function median()

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Mode

This is the last of 3 main measure. Mode returns the most common value found in a list. In the list 2,3,2,4,2 – the mode is 2. Unfortunately R does not have a built in mode function, so for this, we will have build our own function.

For those familiar with functions in programming, this shouldn’t be too foreign of a concept. However, if you don’t understand functions yet, don’t fret. We will get to them soon enough. For now, just read over the code and see if you can figure any of it out for yourself.

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MS SQL Server: Installation

When it comes to SQL Server for personal use – (i.e. training, education) Microsoft offers two options:

  • SQL Server Express: This option is free, but is surprisingly robust. This is the version I cut my teeth on.
  • SQL Server Developer Edition – which you can find online at around the $60.00 price point. This edition is worth the money as it comes with everything  (SSIS, SSRS, etc.) Unfortunately you will need to purchase from a 3rd party vendor because as of the time of this writing, Microsoft is not currently selling it.

For this tutorial, we will focus on Express:

Here is the link for SQL Server Express: Download Link

The screen below explains the options available. You will want – at minimum – to install SQL Server Express with Tools. I would recommend SQL Server Express with Advanced Services.

Select the download arrow my red arrow is pointing to and you will be asked to sign in with your Microsoft Account. (If you don’t have one, do not worry, they are free – sign up for it).

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On the next screen, choose your version and language. Make sure you choose 64 or 32bit. If you don’t know what version Windows you are running. Go to your Control Panel > Admin Tools > System Configuration You will find your system version there.

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Once the file downloads, just run it like a regular MSI. The only thing you really may not have seen before is asking for authentication method. I always go with Mixed Mode (just make sure to remember the SA password you put in).

If you are having trouble, here is a good You Tube Tutorial for a step by step installation: Link to Video

Okay, now we have SQL Server installed, let’s use it.

Starting SQL Server Management Studio

SQL Server Management Studio is how you will interact with SQL Server.

To open it up, hit Windows Key+R. In the run box type SSMS.

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Since you are trying to connect to the SQL Server you just installed on your computer, enter localhost as Server name. Choose Windows Authentication and hit connect.

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Let’s Make a Database

Once SQL Server Management Studio opens, go to the Object Explorer and right click Databases > New Database

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Let us name the new database SQLIntro and hit okay. Don’t worry about other options at this point.

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From the top bar, select New Query

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Copy and Paste the following script into the Query window that just opened up. Don’t worry about the code at this point. Just know:

  1. Use SQLIntro – tells us to use the database we just created
  2. Create table — we are creating a table called FirstTable with 2 columns Name and Age
  3. We are inserting data (names and ages of 4 people) into our new table

Copy the script below:


Use SQLIntro
go

Create table FirstTable
(Name nvarchar(255),
Age int)
go

Insert into FirstTable (Name, Age)
values (‘Ben’, 40), (‘Chris’, 45), (‘Patrick’, 32), (‘Jordan’, 18)
go


After you paste the data, hit Execute!

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Let’s See Our Data

Go to Object Explorer:

  1. Databases — note you will not have as many databases as you see here. This is my SQL Server I have been working with for the past 3 years.
  2. SQLIntro
  3. Tables
  4. Right Click dbo.FirstTable
  5. Select Top 1000 Rows

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And there you have it, the contents of your first table in your first SQL Server Database

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Tableau: Free and Reduced School Lunch Program

This visualization depicts Free, Reduced, and Full priced lunches served by the the National School Lunch Program (NSLP) in United States Public and Private Non-Profit Schools.

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The sharp rise Free lunches, in conjunction with the sharp decline in Full priced lunches since 2008 hints that the effects of the 2008 economic recession are still being felt.

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Visualization can be found at: Link to Tableau Worksheet

**Data taken from Data.gov: Link to Data File