Category Archives: plotly maps python

Plotly maps python

GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. This page documents Geo outline-based maps, and the Mapbox Layers documentation describes how to configure Mapbox tile-based maps.

Figure go. That said, every configuration option here is equally applicable to non-empty maps created with the Plotly Express px. Plotly Geo maps have a built-in base map layer composed of "physical" and "cultural" i. Various lines and area fills can be shown or hidden, and their color and line-widths specified.

In the default plotly templatea map frame and physical features such as a coastal outline and filled land areas are shown, at a small-scale m resolution:. In certain cases, such as large scale choropleth mapsthe default physical map can be distracting. In this case the layout. For example in the following map we hide all physical features except rivers and lakes, neither of which are shown by default:.

In addition to physical base map features, a "cultural" base map is included which is composed of country borders and selected sub-country borders such as states. Note and disclaimer: cultural features are by definition subject to change, debate and dispute. Plotly includes data from Natural Earth "as-is" and defers to the Natural Earth policy regarding disputed borders which read:. Natural Earth Vector draws boundaries of countries according to defacto status.

We show who actually controls the situation on the ground. To create a map with your own cultural features please refer to our choropleth documentation. Here is a map with only cultural features enabled and styled, at a m resolution, which includes only country boundaries.

See below for country sub-unit cultural base map features:. Geo maps are drawn according to a given map projection that flattens the Earth's roughly-spherical surface into a 2-dimensional space.

The available projections are 'equirectangular''mercator''orthographic''natural earth''kavrayskiy7''miller''robinson''eckert4''azimuthal equal area''azimuthal equidistant''conic equal area''conic conformal''conic equidistant''gnomonic''stereographic''mollweide''hammer''transverse mercator''albers usa''winkel tripel''aitoff' and 'sinusoidal'.

Map projections can be rotated using the layout. The layout. See the choropleth maps documentation for more information.

In addition, the named "scope" of a map defines a sub-set of the earth's surface to draw. The available scopes are: 'world''usa''europe''asia''africa''north america''south america'.

The "usa" scope contains state boundaries at both resolutions, and uses the special 'albers usa' projection which moves Alaska and Hawaii closer to the "lower 48 states" to reduce projection distortion and produce a more compact map. A graticule can be drawn using layout. Skip to content. Permalink Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Sign up. Branch: master. Find file Copy path. Cannot retrieve contributors at this time.Recently, I wanted to visualize data from the last federal election. I live in Duesseldorf, Germany and wanted to know in which districts which party had relative strengths.

Surprisingly, it was a little harder than expected.

plotly maps python

Therefore I would like to share my experiences here. We will go through the following steps together:. Preparation 1. You can follow this tutorial with your own dataset to create your individual map. Here you can take a look at the data from this tutorial:.

You also need a mapbox account for this tutorial. Mapbox provides a flexible geodata API. Using the Mapbox API, we can map our individual data to a scalable world map.

You can create an account at www. You need a individual token to use the mapbox services which be be found under the account settings:. GeoJSON is open standard format for geographical features. Within this standard, storage of data follows a particular structure.

Features can be points, lines, polygons or even combinations of the three types. For example, a polygon, a closed area inside a specific room, might look like this:. However, the data is separated and we must merge it later. First, we import all necessary libraries:.

Now we can read the contents for the URLs:. Both data sources are now available as a nested dictionary. We can now import the relevant election data from the dictionary into a pandas dataframe:.

For further processing with Plotly, we now extract the relevant features from the geodata request:. The list sources contains the coordinates for all parts of the city. We will later hand over this list to the Mapbox object in order to present the respective districts. The IDs of the districts are also extracted from the geodata:. We need the IDs later to allocate the correct colorscales for each party and each district. In order to be able to dynamically color the individual parts of the city later on, we need the range of the respective percentages for each party.

The lightest shade is assigned the lowest value and the highest value the darkest shade.By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information.

I installed plotly on Anaconda, getting the error message both on Jupyter and Spyder respectively:. Do not be afraid of looking through in documentation : here you can find nice and understandable examples how to use plotly properly.

plotly maps python

For example, here you can see how to plot simple bar chart, etc. Check your version first:. If you wish to have the figures rendered online, you will now need to import chart-studio and use. You can read up more on the renderers here. Learn more. Plotly - name 'iplot' is not defined Ask Question. Asked 1 year, 6 months ago. Active yesterday. Viewed 4k times.

Active Oldest Votes. You forgot to import it from plotly. Sunny Patel Sunny Patel 6, 2 2 gold badges 27 27 silver badges 38 38 bronze badges.

How are you calling it calicationoflife? It worked for me.This page documents Mapbox tile-based maps, and the Geo map documentation describes how to configure outline-based maps. The word "mapbox" in the trace names and layout.

If your basemap in layout. This token should be provided in layout.

plotly maps python

If your layout. If you have access to your own private tile servers, or wish to use a tile server not included in the list above, the recommended approach is to set layout. If you omit the below attribute when using this approach, your data will likely be hidden by fully-opaque raster tiles! Here is an example of a map which uses a public USGS imagery map, specified in layout. Here is the same example, with in addition, a WMS layer from Environment Canada which displays near-real-time radar imagery in partly-transparent raster tiles, rendered above the go.

Scattermapbox trace, as is the default:. Here is a map rendered with the "dark" style from the Mapbox service, which requires an Access Token:. Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Everywhere in this page that you see fig. If your figure is created with a px. Scattermapboxgo. Choroplethmapbox or go.

Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas - Matplotlib Tutorial

Densitymapboxthe layout. Geo maps are outline-based maps. Scattergeo or go. Choropleththe layout. Base Maps in layout. Using layout.This page documents Geo outline-based maps, and the Mapbox Layers documentation describes how to configure Mapbox tile-based maps.

Map Configuration and Styling in Python

Figure go. That said, every configuration option here is equally applicable to non-empty maps created with the Plotly Express px. Plotly Geo maps have a built-in base map layer composed of "physical" and "cultural" i. Various lines and area fills can be shown or hidden, and their color and line-widths specified. In the default plotly templatea map frame and physical features such as a coastal outline and filled land areas are shown, at a small-scale m resolution:.

In certain cases, such as large scale choropleth mapsthe default physical map can be distracting. In this case the layout. For example in the following map we hide all physical features except rivers and lakes, neither of which are shown by default:.

Bubble Maps in Python

In addition to physical base map features, a "cultural" base map is included which is composed of country borders and selected sub-country borders such as states. Note and disclaimer: cultural features are by definition subject to change, debate and dispute. Plotly includes data from Natural Earth "as-is" and defers to the Natural Earth policy regarding disputed borders which read:. Natural Earth Vector draws boundaries of countries according to defacto status.

We show who actually controls the situation on the ground. To create a map with your own cultural features please refer to our choropleth documentation. Here is a map with only cultural features enabled and styled, at a m resolution, which includes only country boundaries.

See below for country sub-unit cultural base map features:. Geo maps are drawn according to a given map projection that flattens the Earth's roughly-spherical surface into a 2-dimensional space. The available projections are 'equirectangular''mercator''orthographic''natural earth''kavrayskiy7''miller''robinson''eckert4''azimuthal equal area''azimuthal equidistant''conic equal area''conic conformal''conic equidistant''gnomonic''stereographic''mollweide''hammer''transverse mercator''albers usa''winkel tripel''aitoff' and 'sinusoidal'.

Map projections can be rotated using the layout. The layout. See the choropleth maps documentation for more information. In addition, the named "scope" of a map defines a sub-set of the earth's surface to draw.

The available scopes are: 'world''usa''europe''asia''africa''north america''south america'. The "usa" scope contains state boundaries at both resolutions, and uses the special 'albers usa' projection which moves Alaska and Hawaii closer to the "lower 48 states" to reduce projection distortion and produce a more compact map.

A graticule can be drawn using layout. Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Everywhere in this page that you see fig. If your figure is created with a px.For more info about the coronavirus, see cdc. Note from the editors: Towards Data Science is a Medium publication primarily based on the study of data science and machine learning.

We are not health professionals or epidemiologists, and the opinions of this article should not be interpreted as professional advice. To learn more about the coronavirus pandemic, you can click here.

The installation guide can be found on the official webpage. Novel Corona Virus Dataset. In this section, we are going to use plotly. Code explanation.

Line 1—2: import Pandas and Plotly library. Line 4 : Use the Pandas head method to show the first five row of records. From the result above, we can observe the dataset includes the number of reported COVID cases for each country from 22 Jan till 13 April as of this writing.

This dataset is updated on a daily basis. To ease our subsequent task to manipulate the column and plot the map, this is recommended to simplify some column names e. Line 6 : We use the Pandas head method to view the records again after renaming the columns. We can now proceed to use Python Plotly library to create a scatter plot on a map using plotly. The codes Line 8 - 39 can seem daunting in the first place. Here I will only discuss several important parameters.

Line 8 : Set text elements that will appear over the data points. This means when we hover over a data point on the map, the predefined text e. Line 10—11 : lon and lat are the parameters that we set for longitude and latitude of each data point on the map. Line 14—23 : marker is a representation of data points on the map.

Here we set the symbol Line 19 as square. This will render each data point as a square on the map. We can leave the reversescale and autocolorscale as True to enable the color of markers automatically changed by the number of reported COVID cases.

Interactive Choropleth Maps With Plotly

Line 24—26 : cmin and cmax are the lower bound and upper bound of the color domain for the data points. Line 31—37 : This is the part where we set the parameter values for the entire map such as the map title Line 32 and more importantly the scope Line We can pick one of the following scope options:. Line 39 : fig. The markers with yellowish color reflect the relatively lower reported cases compared with those darker colors. From the map, we can see the US hits the most reported cases and it is followed by some countries in Europe such as Italy, UK, French, etc.

When we hover over a data point on the map, we can see a predefined pop up text which reveals the country name and number of reported cases associated with that data point. We can also use the same dataset to plot a choropleth map using plotly. However, we will need to preprocess our data before we can proceed to create the choropleth map.

To create the choropleth map, we need to derive two info from our dataset:. Just look closely at our dataset again by previewing some records.In this article and another few, I will explore Python and Plotly to put together a few different awesome looking charts. You can follow along with the source code that I use, and the data, from this GitLab repository.

I often read articles, like food blogs, or travel blogs, and think: where exactly are these places? Over the last Christmas break, I had the opportunity to travel back to Sydney with my partner, who had never been to Australia, let alone Sydney. So I read a few travel blogs to see what first-time visitors loved about Sydney. It struck me in doing so that a visitor would be easily confused about where everything was and which sights are worth seeing.

My solution to all this was to plot a map, with three goals in mind:. Plotly has my go-to visualisation library for anything custom. I had seen that it includes an amazing MapBox integration, which I had not tried before. So I thought I would kill the proverbial two birds with one stone. If you do not have a Mapbox token, set one up with them — we are going to want to need it. They offer a very free account with very reasonable access limits.

I save my key in a file, and load it in with:. It was slightly painful to collate this information, despite using NLP tools due to people insisting on misspelling names on their blog, or simply calling things by different names. This file includes data for all unique locations that we're going to look at. Load the csv file into a dataframe, and take a look at its contents:. They are the index number, location name string, latitude and longitude in decimals and the type of location.

Indeed they are! I remember that the NaN values are those which I couldn't come up with a category for. Let's give them a name, Misc for miscellaneous. By this stage, we actually already have enough information to plot something! Through the magic of plotly, we just need these lines of code for our first map:. Something like this should have opened on your browser or in your Jupyter notebook. It took just three lines of code to plot this. Plotly Express makes it much faster to create plots.

The map is interactive, so have a look zooming, panning, looking at the markers and isolating each plot by clicking on the legends. Using the open-street-map style means that a mapbox key is not needed, Open Street Map being a free, collaborative project.

While playing with the map, you probably noticed the mouseover tooltips. I also thought the colourful map was a little distracting from the overlays, so I change the mapbox style to lightand now we need to provide the mapbox key. Lastly, I thought the map was initially too high up, when I am mostly interested in the Sydney metro area.

So let's change the default mapped area by specifying the zoom parameter.


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