Develop Reference

Why are my Matplotlib subplots sized differently?

Hello there!
I am trying to create a figure consisting of a chloropleth map and a bar plot in Matplotlib. To achieve this, i am using the Geopandas library alongside Pandas and Matplotlib. I've run into an interesting problem that i couldn't find any answer for on the internet. Here's the problem:
This link leads to an image that replicates the problem.
As it can be seen on the image above, the map on the top (generated by Geopandas) does not span the same width as the bar chart on the bottom. There is too much whitespace to the left and the right of the figure. I want to get rid of this whitespace and make the map fit horizontally on the space that is allocated to it. I am also leaving a code sample below for those who wish to recreate it:
fig = plt.figure(figsize = (25.60,14.40)) #Here, i am setting the overall figure size
ax_1 = fig.add_subplot(2,1,1) #This will be the map
istanbul_districts.plot(ax = ax_1,
edgecolor = "black",
alpha = 1,
color = "Red") #Istanbul_districts is a GeoDataFrame object.
ax_2 = fig.add_subplot(2,1,2)
labels = list(health.loc[:,"district_eng"].value_counts().sort_values(ascending = False).index)
from numpy import arange
bar_positions = arange(len(labels)) + 1
bar_heights = h_inst_per_district_eng.loc[:,"health_count"].values.astype(int)
ax_2.bar(bar_positions,bar_heights,
width = 0.7,
align = "center",
color = "blue") #This is a generic barplot from Matplotlib
I am leaving a second image that shows the end result of the code snippet above:
This link also leads to an image that replicates the problem.
It can be clearly seen above that the axes of the two subplots do not start and end on the same location. Perhaps that could be the problem? What can be done to make them the same size?
Thanks to all those answer for their time in advance!

Adding an explanation, since you have found one solution.
If you specify matplotlib figure with two axes in a way you did, you get the figure split in half. Both axes are the same. Let's say that the original ratio of the figure is 1:1, your axes will be both 1:2.
This arbitrary ratio is fine for a bar chart, which can be scaled to essentially any ratio. It does not matter much if it is horizontal or vertical (from a plotting perspective, not data-viz).
However, if you want your map to show correct non-distorted shapes, you can't just specify the aspect ratio. That just follows the data. So if you have a map, which bounding box has 1:1 ratio, you can't expect that it will fill the whole 1:2 axis. GeoPandas changes the aspect ratio to follow the map's ratio.
The reason why the first example leaves gaps on side and the "solution" does not is this. Because the leftover space is on top and on the bottom the axis, it is not shown in the solution. Because it is on sides in the issue, it just stays there. If you had your plots next to each other instead of above, it would be vice versa.
Hope it is clearer.

Hello again!
swatchai's comment set me up on the right track and i found the culprit. Simply adjusting the figsize to a value like (19,19) fixed the problem. I'd still be happy if anyone can explain exactly why this happens.
Here's what it looks like when the figsize is a square (19,19):
Thanks for your efforts!

Colorbar for each row in ImageGrid

Disclaimer: I am very inexperienced using matplotlib and python in general.
Here is the figure I'm trying to make:
Using GridSpec works well for laying out the plots, but when I try to include a colorbar on the right of each row, it changes the size of the corresponding subplot. This seems to be a well known and unavoidable problem with GridSpec. So at the advice of this question: Matplotlib 2 Subplots, 1 Colorbar
I've decided to remake the whole plot using ImageGrid. Unfortunately the documentation only lists the options cbar_mode=[None|single|each] whereas I want 1 colobar per row. Is there a way to do this inside a single ImageGrid? or will I have to make 2 grids and deal with the nightmare of alignment.
What about the 5th plot at the bottom? Is there a way to include that in the image grid somehow?
The only way I can see this working is to somehow nest two ImageGrids into a GridSpec in a 1x3 column. this seems overly complicated and difficult so I don't want to build that script until I know its the right way to go.
Thanks for any help/advice!

Ok I figured it out. It seems ImageGrid uses subplot somehow inside it. So I was able to generate the following plot using something like
TopGrid = ImageGrid( fig, 311,
nrows_ncols=(1,2),
axes_pad=0,
share_all=True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad=0.0,
cbar_set_cax=True
)
<Plotting commands for the top row of plots and colorbar>
BotGrid = ImageGrid( fig, 312,
nrows_ncols=(1,2),
axes_pad=0,
share_all=True,
cbar_location="right",
cbar_mode="single",
cbar_size="3%",
cbar_pad=0.0,
)
<Plotting commands for bottom row . . .>
StemPlot = plt.subplot(313)
<plotting commands for bottom stem plot>
EDIT: the whitespace in the color plots is intentional, not some artifact from adding the colorbars

Changing the marker on the same set of data

I have a set of data that comes from two different sources, and I have multiple sets graphed together. So essentially 6 scatterplots with error bars (all different colors), and each scatterplot has two sources.
Basically I want the blue scatterplot to have two different markers, 'o' and's'. I currently have done this by plotting each point individually with a loop and checking to see if the source is 1 or 2. If it is 1 it plots a 's' if the source is 2 then it plots a 'o'.
However this method does not really allow for having a legend. (Data1, Data2,...Data6)
Is there a better way of doing this?
EDIT:
I want a cleaner method for this, something along the lines of
x=[1,2,3]
y=[4,5,6]
m=['o','s','^']
plt.scatter(x,y,marker=m)
But this returns an error Unrecognized marker style

A more pythonic way (but still a loop) might be something like
x=[1,2,3]
y=[4,5,6]
l=['data1','data2','data3']
m=['ob','sb','^b']
f,a = plt.subplots(1,1)
[a.plot(*data, label=lab) for data,lab in zip(zip(x,y,m),l)]
plt.legend(loc='lower right')
plt.xlim(0,4)
plt.ylim(3,7);
But I guess this is not the most efficient way if you have lots of datapoints.
If you want to use scatter try something like
m=['o','s','^']
f,a = plt.subplots(1,1)
[a.scatter(*data, marker=m1, label=l1) for data,m1,l1 in zip(zip(x,y),m,l)]
I'm pretty sure, there is also a possibility to apply ** and dicts here.
UPDATE:
Instead of looping over the plot command the ability of matplotlib's plot function to read an arbitrary number of x,y,fmt groups, see docs.
x=np.random.random((3,6))
y=np.random.random((3,6))
l=['data1','data2','data3']
m=['ob','sb','^b']
plt.plot(*[i[j] for i in zip(x,y,m) for j in range(3)])
plt.legend(l,loc='lower right')

Calling plot in a loop is fine. You just need to keep the list of lines returned by plot and use fig.legend to create a legend for the whole figure. See http://matplotlib.org/examples/pylab_examples/figlegend_demo.html

Seconded to #tcaswell 's comments, .scatter() returns collections.PathCollection, which provides a fast way of plotting a large number of identical shaped objects. You can use a loop to plot the data as many scatter plots (and many different datasets) but in my opinion it looses all the speed benefit provided by .scatter().
With these being said, it is however not true that the dots have to be identical in a scatter plot. You can have different linewidth, edgecolor and many other things. But the dots have to be the same shape. See this example, assigning different colors (and only plot one dataset):
>>> sc=plt.scatter(x, y, label='test')
>>> sc.set_color(['r','g','b'])
>>> plt.legend()
See details in http://matplotlib.org/api/collections_api.html.

These were all alright, but not really what I was looking for. The problem was how I parsed through my data and how I could add a legend in the wouldn't mess that up. Since I did a for-loop and plotted each point individually based on if it was measured at Observation location 1 or 2 whenever I made a legend it would plot over 50 legend entries. So I plotted my data as full sets (Invisibly and with no change in symbols) then again in color with the varying symbols. This worked better. Thanks though

Add graph description under graph in pylab [duplicate]

This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Is there a way of drawing a caption box in matplotlib
Is it possible to add graph description under graph in pylab?
Let's say that I plot the following graph:
import pylab
x = [1,2,3,2,4,5,6,4,7,8]
pylab.plot(x)
pylab.title('My Plot')
pylab.xlabel('My x values')
pylab.ylabel('My y values')
pylab.show()
I also want to insert a few lines that describe the graph, perhaps something like this (not real code):
pylab.description('Figure 1.1 is designed for me to learn basics of Pylab')
Is that possible?
Also, I am vague on differences between pylab and matplotlib, so if there is a solution that works when using matplotlib, it will probably work.
Thank You in Advance

figtext is useful for this since it adds text in the figure coordinates, that is, 0 to 1 for x and y, regardless of the axes. Here's an example:
from pylab import *
figure()
gca().set_position((.1, .3, .8, .6)) # to make a bit of room for extra text
plot([1,2], [3,4])
figtext(.95, .9, "This is text on the side of the figure", rotation='vertical')
figtext(.02, .02, "This is text on the bottom of the figure.\nHere I've made extra room for adding more text.\n" + ("blah "*16+"\n")*3)
xlabel("an interesting axis label")
show()
Here I've used axes.set_position() to make some extra room on the bottom of the figure by making the axes a bit smaller. Here I added room for lots of text and also so the text doesn't bump into the axes label, though it's probably a bit excessive.
Although you asked for text on the bottom, I usually put such labels on the side, so they are more clearly notes and not part of the figure. (I've found it useful, for example, to have a little function that automatically puts the name of the file that generated each figure onto the figure.)

Matplotlib questions [duplicate]

This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Plotting with Python
I've been using Matprolib for plotting. I've found it very useful, but I dont know exactly how to use the 'fill_between()' function. I have tried several times to fix it but I cant get to the point.
I have been studying several tutorials, but I havent found very useful ones (according to my task).
My task is to fill the area that all lines have in common, just like this:
Whatitshoulddo
And this is what the system does:
Whatitshouldntdo
Is there any way to do it? Anyone knows how to use 'fill_between()' in a correct way?

You can use the where option. As in the example you can do something like:
fill_between(x, myzero, y1, where=y2>=y1, facecolor='blue', interpolate=True)
Where y2 is the line that is sometimes on top. You will have do do this for each of the lines, though.
Another option is to define a minimum of the functions and fill below that, though you will either need to know before hand that the ys are defined at the same points or use interpolation so that they are all defined at the same points.
mymin = np.minimum(y1,y2,y3)
fill_between(x, myzero, mymin)
Hope that helps.
Edit: To find the minimum from several functions which are all defined for the same x-values you can use the following:
def OverallMinimum(*ys):
mymin = y[0].copy()
for y in ys:
min = np.minimum(mymin,y)
return mymin
Then you can use the second fill_between from above to plot between zero and the minimum from that function.