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)