def test_stat_bin(): x = [1, 2, 3] y = [1, 2, 3] df = pd.DataFrame({'x': x, 'y': y}) # About the default bins gg = ggplot(aes(x='x'), df) + stat_bin() with pytest.warns(None) as record: gg.draw_test() res = ('bins' in str(item.message).lower() for item in record) assert any(res) # About the ignoring the y aesthetic gg = ggplot(aes(x='x', y='y'), df) + stat_bin() with pytest.raises(PlotnineError): gg.draw_test()
def test_stat_bin(): x = [1, 2, 3] y = [1, 2, 3] df = pd.DataFrame({'x': x, 'y': y}) # About the default bins gg = ggplot(aes(x='x'), df) + stat_bin() if not six.PY2: # Test fails on PY2 when all the tests are run, # but not when only this test module is run with pytest.warns(None) as record: gg.draw_test() res = ('bins' in str(item.message).lower() for item in record) assert any(res) # About the ignoring the y aesthetic gg = ggplot(aes(x='x', y='y'), df) + stat_bin() with pytest.raises(PlotnineError): gg.draw_test()
# # (C) Copyright 2021 Pavel Tisnovsky # # All rights reserved. This program and the accompanying materials # are made available under the terms of the Eclipse Public License v1.0 # which accompanies this distribution, and is available at # http://www.eclipse.org/legal/epl-v10.html # # Contributors: # Pavel Tisnovsky # from plotnine.data import economics from plotnine import ggplot, aes, geom_bar, stat_bin g = ggplot(economics) + aes(x="uempmed") + stat_bin(bins=20) + geom_bar() g.save("15.png")
from plotnine.data import mtcars from plotnine import ggplot, aes, geom_bar, stat_bin print(ggplot(mtcars) + aes(x="hp") + stat_bin(bins=12) + geom_bar())
import numpy as np import pandas as pd import statsmodels.api as sm import statsmodels.formula.api as smf from itertools import combinations import plotnine as p # read data import ssl ssl._create_default_https_context = ssl._create_unverified_context def read_data(file): return pd.read_stata( "https://raw.github.com/scunning1975/mixtape/master/" + file) training_example = read_data("training_example.dta") p.ggplot(training_example, p.aes(x='age_treat')) + p.stat_bin(bins=10) p.ggplot(training_example, p.aes(x='age_control')) + p.geom_histogram(bins=10)