8000 DOC: sphinx-gallery histograms by choldgraf · Pull Request #8245 · matplotlib/matplotlib · GitHub
[go: up one dir, main page]
Skip to content

DOC: sphinx-gallery histograms #8245

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
NelleV merged 3 commits into from
Mar 10, 2017
Merged

DOC: sphinx-gallery histograms #8245

Changes from 1 commit
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
eba8ab1
combining and updating 2d hist examples
choldgraf Mar 8, 2017
397c76b
consolidating histogram examples and moving to SG folder
choldgraf Mar 8, 2017
77c16fb
addressing small change comments
choldgraf Mar 10, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
addressing small change comments
  • Loading branch information
@choldgraf
choldgraf authored Mar 10, 2017
commit 77c16fb3175897cae8308a688e30756b4d0647ec
9 changes: 5 additions & 4 deletions examples/statistics/plot_hist.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@
#
# To generate a 1D histogram we only need a single vector of numbers. For a 2D
# histogram we'll need a second vector. We'll generate both below, and show
# the histogram for each vector
# the histogram for each vector.

N_points = 100000
n_bins = 20
Expand All @@ -44,7 +44,7 @@
# The histogram method returns (among other things) a `patches` object. This
# gives us access to the properties of the objects drawn. Using this, we can
# edit the histogram to our liking. Let's change the color of each bar
# based on its y value
# based on its y value.

fig, axs = plt.subplots(1, 2, figsize=(10, 5), tight_layout=True)

Expand All @@ -62,7 +62,7 @@
color = plt.cm.viridis(norm(thisfrac))
thispatch.set_facecolor(color)

# We can also normalize our inputs by the total number of counts.
# We can also normalize our inputs by the total number of counts
axs[1].hist(x, bins=n_bins, normed=True)

# Now we format the y-axis to display percentage
Expand All @@ -79,12 +79,13 @@
fig, ax = plt.subplots(tight_layout=True)
hist = ax.hist2d(x, y)


###############################################################################
# Customizing your histogram
# --------------------------
#
# Customizing a 2D histogram is similar to the 1D case, you can control
# visual components such as the bin size or color normalization
# visual components such as the bin size or color normalization.

fig, axs = plt.subplots(1, 3, figsize=(15, 5), sharex=True, sharey=True,
tight_layout=True)
Expand Down
0