{"id":13282,"date":"2021-02-26T16:32:00","date_gmt":"2021-02-26T16:32:00","guid":{"rendered":"https:\/\/www.askpython.com\/?p=13282"},"modified":"2021-03-09T16:32:48","modified_gmt":"2021-03-09T16:32:48","slug":"build-a-dashboard-in-python","status":"publish","type":"post","link":"https:\/\/www.askpython.com\/python\/examples\/build-a-dashboard-in-python","title":{"rendered":"Build a dashboard in python from a CSV file [ Easy Steps ]"},"content":{"rendered":"\n

Hello readers! In this tutorial, we’ll be looking at how we can quickly build a dashboard in Python using dash, from a CSV file.<\/p>\n\n\n\n

Dash is a Python framework that makes it easy for anyone to build dashboards in Python, while not having to deal with the frontend required directly.<\/p>\n\n\n\n

Steps to build a dashboard in Python<\/h2>\n\n\n\n

Let’s now get started and build a dashboard in Python using the dash library to display data from a CSV File!<\/p>\n\n\n\n

Step 1: Plot the data using Plotly<\/h3>\n\n\n\n

We’ll be using a simple CSV file for the data source, namely a COVID time series dataset.<\/p>\n\n\n\n

I’m using this<\/a> COVID-19 dataset from Kaggle. Once you have it ready, we can start using it.<\/p>\n\n\n\n

To render the plots, we’ll be using the Python plotly library<\/a>. To install this library, use:<\/p>\n\n\n

\npip install plotly\n<\/pre><\/div>\n\n\n
Let’s now plot the time series data for various states. We’ll use the Pandas read_csv() function<\/a> to read the data from our CSV dataset. It’s just 3 simple lines of code!<\/p>\n\n\n
\nimport plotly.express as px\n\ndf = pd.read_csv('covid_19_india.csv')\n\n# Plot the scatterplot using Plotly. We ploy y vs x (#Confirmed vs Date)\nfig = px.scatter(df, x='Date', y='Confirmed', color='State\/UnionTerritory')\nfig.update_traces(mode='markers+lines')\nfig.show()\n<\/pre><\/div>\n\n\n
Now plotly should give you a nice visualization of the data. Let’s now render this in our Dash application.<\/p>\n\n\n\n
Step 2: Embed the graph with Dash<\/h3>\n\n\n\n
To render our dashboard application, we’ll be using Dash<\/a>. Install this library using:<\/p>\n\n\n
\npip install dash\n<\/pre><\/div>\n\n\n
We’ll use dash to render the data in a layout.<\/p>\n\n\n\n
Before that, let’s set up some stylesheets (CSS) for our page to look good! I’m using the default data from this<\/a> dash official tutorial.<\/p>\n\n\n
\nimport dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nimport plotly.express as px\nimport pandas as pd\n\nexternal_stylesheets = ['https:\/\/codepen.io\/chriddyp\/pen\/bWLwgP.css']\n\napp = dash.Dash(__name__, external_stylesheets=external_stylesheets)\n\ncolors = {\n    'background': '#F0F8FF',\n    'text': '#00008B'\n}\n<\/pre><\/div>\n\n\n
Let’s now configure our data in this layout.<\/p>\n\n\n
\n# Our dataframe\ndf = pd.read_csv('covid_19_india.csv')\n\nfig = px.scatter(df, x='Date', y='Confirmed', color='State\/UnionTerritory')\nfig.update_traces(mode='markers+lines')\n\napp.layout = html.Div(children=[\n    html.H1(children='COVID-19 Time Series Dashboard'),\n\n    html.Div(children='''\n        COVID-19 Dashboard: India.\n    '''),\n\n    dcc.Graph(\n        id='example-graph',\n        figure=fig\n    )\n])\n<\/pre><\/div>\n\n\n
Step 3: Run the application server with Flask<\/h3>\n\n\n\n
Now, let’s finally run the application server (via Flask<\/a>):<\/p>\n\n\n
\nif __name__ == '__main__':\n    app.run_server(debug=True)\n<\/pre><\/div>\n\n\n
This will start the server on local port 8050. Let’s look at the output now, when we go to http:\/\/localhost:8050<\/code><\/p>\n\n\n\n
\"Dashboard
Dashboard Output<\/figcaption><\/figure><\/div>\n\n\n\n
As you can see, we indeed have a nice looking interactive dashboard in just a few lines of Python code!<\/p>\n\n\n\n
\n\n\n\n
Conclusion<\/h2>\n\n\n\n
In this tutorial, we learned how we could build a dashboard in Python from a CSV file using Dash.<\/p>\n\n\n\n
\n","protected":false},"excerpt":{"rendered":"
Hello readers! In this tutorial, we’ll be looking at how we can quickly build a dashboard in Python using dash, from a CSV file. Dash is a Python framework that makes it easy for anyone to build dashboards in Python, while not having to deal with the frontend required directly. Steps to build a dashboard […]<\/p>\n","protected":false},"author":7,"featured_media":13286,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-13282","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-examples"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/13282","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/comments?post=13282"}],"version-history":[{"count":0,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/posts\/13282\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media\/13286"}],"wp:attachment":[{"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/media?parent=13282"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/categories?post=13282"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.askpython.com\/wp-json\/wp\/v2\/tags?post=13282"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}