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diff --git a/content/blog/2024-01-27-tableau-dashboard.md b/content/blog/2024-01-27-tableau-dashboard.md deleted file mode 100644 index 3fa0d50..0000000 --- a/content/blog/2024-01-27-tableau-dashboard.md +++ /dev/null @@ -1,148 +0,0 @@ -+++ -date = 2024-01-27 -title = "Data Visualization: Mapping Omaha Crime Data with Tableau" -description = "" -draft = false -+++ - -In this project, I am going to show you how to use Tableau Public for free to -create simple dashboards. - -I will be creating simple visuals from an Omaha crime data set and combining -them to create the dashboard below. You can view this dashboard interactively -online here: [Omaha Crime Data (2015 - -2023)](https://public.tableau.com/app/profile/c.c7042/viz/OmahaCrimeData2015-2023/OmahaCrimeData2015-2023#1). - - - -# Gather the Data - -You can download incident data from the Omaha Police Department on their -[Incident Data -Download](https://police.cityofomaha.org/crime-information/incident-data-download) -page. They currently have files for the years 2015 through 2023. - -Each file will be downloaded as a CSV file, approximately 3 MB - 8 MB. - -# Clean and Transform the Data - -I have used Python to combine the files into a single CSV file, as well as -adding a custom `datetime` column. You could do this step in any software you -prefer, but I prefer Python as its free, easy to use, and has a plethora of -support resources online. - -Start by opening a terminal, navigating to your Downloads directory, and -creating a python script. - -```sh -cd ~/Downloads -nano data_processing.py -``` - -Within the Python script, paste the following: - -```python -# Import modules -import pandas as pd -import glob -import os - -# Import the data -path = r"~/Downloads/*.csv" -files = glob.glob(path) - -list = [] - -for file in files: - df_tmp = pd.read_csv(file) - li.append(df_tmp) - -df = pd.concat(list, axis=0, ignore_index=True) - -# Create a combined datetime column -df["datetime"] = pd.to_datetime( - df["date"] + " " + df["time"], - format="%m/%d/%Y %H:%M:%S" -) -df.head() - -# Export the combined data -df.to_csv(r"~/Downloads/combined_incidents.csv") -``` - -Once pasted, save and close the file. You can execute the file like so: - -```sh -python3 data_processing.py -``` - -After this, you should have a combined data file that contains all incidents -between 2015 and 2023. Mine was approximately 55 MB. - -# Tableau Public - -[Tableau Public](https://public.tableau.com/) is a free-to-use web application -that allows you to create visualizations by uploading data sources. Note that -there's no way to keep the data and visualizations private, so don't upload -anything private. - -After creating an account, you can click the `Create` > `Web Authoring` link to -create your first visualization. - -## Upload the Data - -Once you've opened your first project, Tableau will ask you to connect to your -data. For this project, click the `Upload from computer` button and select the -CSV file previously combined in the step above. - -Once connected, you can refresh the preview of the data with the `Refresh Data -Source` button in the toolbar. - -If you need to edit any of the data types, column names, etc., you can do so -now. Once complete, generate an extract so that you can start creating -visualizations. - -## Create Visualizations - -To start, create a worksheet in the toolbar at the bottom of the screen. - -Within this screen, select a column from the `Data` side bar on the left and -drag it into the `Columns` or `Rows` area of the canvas. - -See below for the map visualization. You can recreate this by adding the -following fields: - -- `Columns`: Lon -- `Rows`: Lat -- `Marks`: - - Description - - Datetime -- `Filters`: Datetime - -You can repeat this process for each visualization you want to create. Explore -your options by dragging data fields to different areas and by opening the field -options to explore what operations can be performed on different data types -(e.g., average, count, etc.). - -## Create Dashboard - -To create a dashboard, click the button on the toolbar at the bottom of the -screen. Within the dashboard, drag each sheet from the left side bar onto the -dashboard canvas. - -## Formatting - -You can explore a ton of different formatting options throughout the worksheets -and dashboard. Specifically for maps, you can alter the map layers, background, -and visible features through the `Map` menu in the top file menu of the editing -screen. - -In the finished dashboard below, I opted for a dark mode with a map that showed -county lines and city names. - -There's a ton of other options available to be used in a dashboard like this, -but this project shows a quick preview of what you can do in Tableau Public. - - |