import pyqtgraph as pg
from PyQt4 import QtGui
import pandas
from datos import data
win = pg.GraphicsWindow("Dot Matrix ")
win.resize(300,300)
v = win.addViewBox()
v.setAspectLocked()
text = pg.TextItem("Dot Matrix by Number of Gears ", anchor=(-0.1,22.5), color='w')
v.addItem(text)
d=data('mtcars')
ps = pandas.Series([i for i in d.gear])
counts = ps.value_counts()
position=[ (-0.5,15), (-2,15), (-3.5,15)]
colours = [QtGui.QColor('springgreen'), QtGui.QColor('lightskyblue'), QtGui.QColor('lightcoral')]
x=0.0
y=1.0
m=0
cols=1
for i in counts:
for j in range(i):
ellipse = QtGui.QGraphicsEllipseItem(x,y,0.05,0.05)
ellipse.setBrush(colours[m])
v.addItem(ellipse)
x=x+0.05
cols=cols+1
if (cols>10):
cols=1
import seaborn as sns
import matplotlib.pyplot as plt
from datos import data
import pandas
sns.set(style="whitegrid")
f, ax = plt.subplots(figsize=(6, 15))
d = data('mtcars')
t1 = d.pivot_table(values='carb', index=['cyl'], columns=['gear'], aggfunc=len)
bar_width = 0.4
sns.barplot(x=t1.columns,
y=t1.values[0] + t1.values[1] + t1.values[2],
label="8 ",
color="#2ecc71")
sns.barplot(x=t1.columns,
y=t1.values[0] + t1.values[1],
label="6 ",
color="salmon")
sns.barplot(x=t1.columns, y=t1.values[0], label="4 ", color="skyblue")
ax.legend(ncol=1, loc="center right", title="Cylindres")
sns.despine(bottom=True)
plt.title('Car Distribution by Gear and Cylindres', family='Serif', size=16)
plt.show()
import matplotlib
import matplotlib.pyplot as plt
from scipy.stats import t
import datos as dpl
import math
from scipy import stats
#import pandas as pd
import csv
import sys
#from mpl_toolkits.basemap import Basemap
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from scipy.optimize import curve_fit
import scipy
data = dpl.data("DATA")
valor = []
valor1 = []
valor2 = []
residuos = []
proba_incidencia = []
pr = []
gen_residuos = []
dis_residuos = []
#---------------generacion-disposicion de residuos solidos=total de residuos
for i in range(len(data.gen_residuos)):
residuos.append([
data.gen_residuos[i][0],
float(data.gen_residuos[i][1]) - float(data.dis_residuos[i][1])
])
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
from datos import data
d = data("mtcars")
app = QtGui.QApplication([])
view = pg.GraphicsView()
l = pg.GraphicsLayout(border=(100, 100, 100))
view.setCentralItem(l)
view.show()
view.setWindowTitle('Simple Line Chart Example')
view.resize(800, 600)
p1 = l.addPlot(title="Motor Trend Car Road Tests")
p1.plot(d.am, d.gear)
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
from datos import data
d=data("mtcars")
app = QtGui.QApplication([])
view = pg.GraphicsView()
l = pg.GraphicsLayout(border=(100,100,100))
view.setCentralItem(l)
view.show()
view.setWindowTitle('Simple Line Chart Example')
view.resize(800,600)
p1 = l.addPlot(title="Motor Trend Car Road Tests")
p1.plot(d.am,d.gear)
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
from mpl_toolkits.basemap import Basemap, cm
# requires netcdf4-python (netcdf4-python.googlecode.com)
from netCDF4 import Dataset as NetCDFFile
import numpy as np
import matplotlib.pyplot as plt
import datos as dpl
#----------------------------prueba---------------------------
data1 = dpl.data("DATA")
proba_incidencia = []
for i in range(len(data1.cases)):
proba_incidencia.append([
data1.cases[i][0],
float(data1.cases[i][53]) / float(data1.poblacion[i][1])
])
#p_incidencia = np.array(proba_incidencia[:][1])
p_incidencia = np.array(proba_incidencia).T[1]
print '-------------------'
#----------------map--------------------------------------
from matplotlib.patches import Polygon
from matplotlib.collections import PatchCollection
from matplotlib.colors import rgb2hex
cmap = plt.cm.autumn
fig = plt.figure()
ax = fig.add_subplot(111)
