def getDensityPlot():
X = validate.getdatafile()
X.astype('float32')
pyplot.figure(1)
pyplot.subplot(211)
X.hist()
pyplot.subplot(212)
X.plot(kind='kde')
pyplot.show()
def getBoxWhiskerPlot():
X = validate.getdatafile()
X.astype('float32')
groepen = X['1964':'1970'].groupby(TimeGrouper('A'))
jaren = DataFrame()
for name, groep in groepen:
jaren[name.year] = groep.values
jaren.boxplot()
pyplot.show()
def predictFuture():
series = validate.getdatafile()
months_in_year = 12
model_fit = ARIMAResults.load(variables.model)
bias = numpy.load(variables.bias)
yhat = float(model_fit.forecast()[0])
yhat = bias + inverse_difference(series.values, yhat, months_in_year)
print('Predicted: %.3f' % yhat)
pyplot.plot(series)
pyplot.title('Lijn diagram tot aan voorspelling')
pyplot.show()
prediction = pd.DataFrame(yhat)
prediction.to_csv(variables.predictionSave,
mode='a',
sep=',',
header=False)
prediction.to_csv(variables.datafileloc, mode='a', header=False)
def getSummary():
from Data import validate
file = validate.getdatafile()
summary = file.describe()
print(summary)
def getLineplot():
X = validate.getdatafile()
X.plot()
pyplot.title('Lijn diagram')
pyplot.show()