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author | mattip <matti.picus@gmail.com> | 2018-04-11 14:22:00 +0300 |
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committer | mattip <matti.picus@gmail.com> | 2018-04-11 14:22:00 +0300 |
commit | 0a8ba953cc3fb973f63e2948c1d2027d39b9f88c (patch) | |
tree | b29bbe5e3665c45c553944aac47f3c56f145964f /doc/source/user | |
parent | db93ce93064239a429909a100082940b624c84e8 (diff) | |
download | numpy-0a8ba953cc3fb973f63e2948c1d2027d39b9f88c.tar.gz |
update kwargs where needed
Diffstat (limited to 'doc/source/user')
-rw-r--r-- | doc/source/user/quickstart.rst | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/doc/source/user/quickstart.rst b/doc/source/user/quickstart.rst index 67f45a50f..7e1c381d2 100644 --- a/doc/source/user/quickstart.rst +++ b/doc/source/user/quickstart.rst @@ -1451,10 +1451,10 @@ that ``pylab.hist`` plots the histogram automatically, while >>> mu, sigma = 2, 0.5 >>> v = np.random.normal(mu,sigma,10000) >>> # Plot a normalized histogram with 50 bins - >>> plt.hist(v, bins=50, normed=1) # matplotlib version (plot) + >>> plt.hist(v, bins=50, density=1) # matplotlib version (plot) >>> plt.show() >>> # Compute the histogram with numpy and then plot it - >>> (n, bins) = np.histogram(v, bins=50, normed=True) # NumPy version (no plot) + >>> (n, bins) = np.histogram(v, bins=50, density=True) # NumPy version (no plot) >>> plt.plot(.5*(bins[1:]+bins[:-1]), n) >>> plt.show() |