def test_ordinal_plot():
import matplotlib
matplotlib.use('Agg')
from plotSlope import slope
import numpy as np
import pandas as pd
import os
if os.path.exists('test_ordinal.png'):
os.remove('test_ordinal.png')
df = pd.DataFrame(
np.random.normal(loc=np.ones(shape=[20, 30]) * np.arange(30)))
df.rename(columns=lambda el: str(el),
index=lambda el: str(el),
inplace=True)
f = slope(df.T,
width=10,
height=8,
kind='ordinal',
savename='test_ordinal.png',
dpi=200,
color={
'10': 'red',
'27': 'blue'
},
marker=None)
assert os.path.exists('test_ordinal.png')
if os.path.exists('test_ordinal.png'):
os.remove('test_ordinal.png')
def make_and_save_slope_plot_gs(df):
grade = df.iloc[0]['grade']
subject = df.iloc[0]['subject']
d = df[["school", "boy", "moy"]]
d = d.set_index("school")
f = slope(d,
# Need to manually adjust width and height depending on data
height=16,width=10,font_size=8,
title="MAP Scores for {0}, Grade {1}".format(subject, grade),
font_family='GillSans', color=renew_highlights
)
f.savefig('./../Output/scaled slopegraph map {0} grade {1}.png'.format(subject, grade))
def test_ordinal_plot():
import matplotlib
matplotlib.use('Agg')
from plotSlope import slope
import numpy as np
import pandas as pd
import os
if os.path.exists('test_ordinal.png'):
os.remove('test_ordinal.png')
df = pd.DataFrame( np.random.normal(loc=np.ones(shape=[20,30])*np.arange(30)))
df.rename(columns = lambda el : str(el),index =lambda el : str(el),inplace=True)
f = slope(df.T,width =10,height= 8,kind='ordinal',savename='test_ordinal.png',dpi=200,color={'10':'red','27':'blue'},marker=None)
assert os.path.exists('test_ordinal.png')
if os.path.exists('test_ordinal.png'):
os.remove('test_ordinal.png')
def test_interval_plot():
import matplotlib
matplotlib.use('Agg')
from plotSlope import slope
import pandas as pd
import os
data_EU = pd.read_csv(os.path.join('data', 'EU_GDP_2007_2013.csv'),
index_col=0,
na_values='-')
EU_color = {
"France": 'b',
'Germany': 'r',
'Ireland': 'chocolate',
'United Kingdom': 'purple'
}
if os.path.exists('test_interval.png'):
os.remove('test_interval.png')
f = slope(
data_EU.ix[:, :-3] / 1000,
kind='interval',
savename='test_interval.png',
dpi=200,
height=18,
width=30,
font_size=20,
color=EU_color,
title=
u'European GPD until 2010 and forecasts at market prices (billions of Euro) source : EUROSTAT'
)
assert os.path.exists('test_interval.png')
if os.path.exists('test_interval.png'):
os.remove('test_interval.png')
def test_interval_plot():
import matplotlib
matplotlib.use('Agg')
from plotSlope import slope
import pandas as pd
import os
data_EU = pd.read_csv(os.path.join('data','EU_GDP_2007_2013.csv'),
index_col=0,
na_values='-')
EU_color = {
"France": 'b',
'Germany': 'r',
'Ireland': 'chocolate',
'United Kingdom': 'purple'
}
if os.path.exists('test_interval.png'):
os.remove('test_interval.png')
f = slope( data_EU.ix[:,:-3] / 1000,
kind='interval',
savename='test_interval.png', dpi=200,
height=18,
width=30,
font_size=20,
color=EU_color,
title= u'European GPD until 2010 and forecasts at market prices (billions of Euro) source : EUROSTAT')
assert os.path.exists('test_interval.png')
if os.path.exists('test_interval.png'):
os.remove('test_interval.png')