I am not a programmer but I have been doing some data analysis using Python lately and recently stumbled across Matplotlib. I have a series of geo-coordinate data points that I am trying to visualize. The data consists of geo coordinates and the sqft of each location:
latitude, longitude, SQFT
I have about 25k of these data points and I would like to show the cumulative sqft of these on a 2d image; basically create a heatmap of the sqft. I have managed to use Matplotlib to create a hexbin with the lat and long data but this only gives me a count of the number of times an item falls into the bin. I cannot figure out how I incorporate the sqft into the bins. I have looked at the matplotlib docs and found that I can enter an additional variable, they call C, but I can't figure out how I need to format the data (or if this will even do what I need it to).
Related
I have a polydata file containing 3D coordinates of the mesh (as vtkPoints) and temperature at each point as an attribute. I want to plot the temperature as a slice plot (at three elevations) over the geometry. I managed to get the data slices at different elevation using vtkClipPolyData function. However, I am unable to find a good example showing how to interpolate the value at each of these points and plot the data. Really appreciate if someone can help me on this.
I tried to render the clipped data directly by increasing the point size from actor property,
actor.GetProperty().SetPointSize(5)
however, this gives a pixelated plot. See plot here
I know my question might sound a bit too general but I actually just need some guidance to start learning geographical plotting with Plotly package iin python.
I'm following guides on the internet but I never really manage to replicate the method with data I find on the internet.
The simple case I'm trying to plot is the following:
I have a Geopandas dataframe gdf with coordinates of point samples and a value, all measured in a particular European state (Netherlands in my case).
I found on the internet a shape of the state in json (link to json)
What I am trying to do is:
Plotting a blank choropleth map of the Netherlands, so that it would set the correct position for points of the dataframe
On top of the previous layer, I want to plot the points of my gdf
I'm not asking for code so I won't be posting the gdf.
What I really want to understand is
Is this (px.choropleth overlayed with px.scatter_geo) the best way to plot points on a conventional geographical area?
What are the features that need to be present on my gdf in order to make this work? For now it has a 'geometry' column and a 'value' column.
Also feel free to post any additional resource that might prove helpful to start learning this topic (as long they explain every step and don't assume familiarity with geodata structure).
I have to generate analysis of flight reports. In the chart I'm trying to draw, each point is corresponding to one flight with the Date in X-axis. So, It is possible to have several points for the same X.
Each point represent the aircraft speed at a specific moment in the flight. The pilot did good if the value (IAS in knots) is in the range 80-95. So, I want to show if the pilot is getting better by a running median on 8 values. But, sometime there are multiple flights on the same day so it creates "vertical lines" in the trendline.
I'm using Python on Databricks.
There is my dataset:
And there is the plot:
What is the best way to draw a smooth trend line dealing with Date as X-axis and the multiple points on same X ?
Thanks
I Posted this question about 3D plots of data frames:
3D plot of 2d Pandas data frame
and the user referred me very very helfully to this:
Plotting Pandas Crosstab Dataframe into 3D bar chart
It use useful and the code worked in principle, but it lookes like a mess (see image below) for several reasons:
I have huge number of values to plot (470 or so, along the y-axis) so perhaps a bar chart is not the best way (I am going for a histogram kind of look, so I assumed very narrow bars would be suitable)
my counts (z axis) do not give almost any information, because the differences I need to see are from 100 to the max value
how can I make the 3D plot that shows up interactive? (being able to rotate etc) - I have seen it done in blogs/videos but sure if it's something on Tools -> Preferences that I can't find
So re: the second issue, simple enough, I tried to just change the limits of the zbar as I would for a 2D Plot, by incorporating:
ax.set_zlim([110,150])
just before the axis labels, but obviously this is the wrong way:
SO do I have to limit the values from the original data set (i.e. filter out <110), or is there a way to do this from the plot?
I have a huge data set of time series data. In order to visualise the clustering in python, I want to plot time series graphs along with the dendrogram as shown below.
I tried to do it by using subgrid2plot() function in python by creating two subplots side by side. I filled first one with series graphs and second one with dendrograms. But once number of time series increased, it became blur.
Can someone suggest a nice way to plot this type of dendrogram? I have around 50,000 time series to cluster and visualise.
Convert data into JSON with json module of python and then use D3.js for graph ploting.
Check the Gallery from here where you can find dendrogram and time series graph