def main(): data_dwd, dwd_se = fl.getConnectionDWD() data_wetterdienst, wd_se = fl.getConnectionWetterdienstde() data_wetterde, we_se = fl.getConnectionWetterde() data_wettercom, wc_se = fl.getConnectionWettercom() data_openweather, ow_se = fl.getConnectionOpenWeatherMaporg() data_accuweather, aw_se = fl.getConnectionAccuweathercom() measure_date = 20180604 # x_day_forecast = 1 #Attention: 20180630 - 2018071 != 1 ... tuple_without_dwd = [(data_openweather, ow_se),(data_accuweather, aw_se), (data_wetterdienst, wd_se), (data_wettercom, wc_se)] boxPlot_maxtemp(tuple_without_dwd, measure_date, x_day_forecast) boxplot_mintemp(tuple_without_dwd, measure_date, x_day_forecast) boxplot_sunhours(tuple_without_dwd, measure_date, x_day_forecast) boxplot_windspeed(tuple_without_dwd, measure_date, x_day_forecast) plot_mintemp(tuple_without_dwd, measure_date, x_day_forecast) plot_maxtemp(tuple_without_dwd, measure_date, x_day_forecast) plt.show()
import pandas as pd
import numpy as np
import sys
#sys.path.append("C:/Users/Lukas Tilmann/mkp_database")
sys.path.append('/Users/kyrak/PycharmProjects/MKP/')
import FunctionLibraryExtended as fl
dwd, se = fl.getConnectionDWD()
acc, se_acc = fl.getConnectionAccuweathercom()
op, se_op = fl.getConnectionOpenWeatherMaporg()
wc, se_wc = fl.getConnectionWettercom()
wd, se_wd = fl.getConnectionWetterdienstde()
'''
Data available - copied from Slack:
1 - es gibt einen Eintrag
0 - Null
accuweather openweathermapporg wettercom wetterdienstde
measure_date 1 1 1 1
measure_date_hour 1 1 1 1
measure_date_prediction 1 1 1 1
measure_date_prediction_hour 1 1 1 1
postcode 0 1 1 1
city 1 1 0 0
temp 0 1 0 0
def boxPlotAvgTemp():
'''
dimension represents data values (columns of service provider) which will be plotted
Plots compare dwd data with each service provider of weather data
Not recommended to plot "cloud" because of its natural appearance (x/8)'''
data_dwd, dwd_se = fl.getConnectionDWD()
data_wetterdienst, wd_se = fl.getConnectionWetterdienstde()
data_wetterde, we_se = fl.getConnectionWetterde()
data_wettercom, wc_se = fl.getConnectionWettercom()
data_openweather, ow_se = fl.getConnectionOpenWeatherMaporg()
data_accuweather, aw_se = fl.getConnectionAccuweathercom()
#session_list = []
#session_list.extend([wd_se, wc_se, ow_se, aw_se])
#table_list = []
#table_list.extend([data_wetterdienst, data_wetterde, data_wettercom, data_openweather, data_accuweather])
tuple_list = [(data_openweather, ow_se),(data_accuweather, aw_se), (data_wetterdienst, wd_se), (data_wetterde, we_se), (data_wettercom, wc_se)]
dataList = []
for (table, se) in tuple_list :
wetterdienst_maxTemp = fl.getResult(se.execute('SELECT max_temp FROM ' + str(table)), se)
wetterdienst_minTemp = fl.getResult(se.execute('SELECT min_temp FROM ' + str(table)), se)
wetterdienst_avgTemp = (wetterdienst_maxTemp*58 + wetterdienst_minTemp* 42)/100 #Juni18 überd. warm, 13 Sonnenstunden ca. => gew. Temp
dataList.append(wetterdienst_avgTemp)
print(dataList[0])
#data_dwd = pd.read_sql('SELECT dimension FROM dwd', con = fl.getConnectionDWD))
#data_wetterdienst = pd.read_sql('SELECT dimension FROM wetterdienstde', con = fl.getConnectionWetterdienstde))
#data_wetterde = pd.read_sql('SELECT dimension FROM wetterde', con = fl.getConnectionWetterde))
#data_wettercom = pd.read_sql('SELECT dimension FROM wettercom', con = fl.getConnectionWettercom))
#data_openweather = pd.read_sql('SELECT dimension FROM openweathermaporg', con = fl.getConnectionOpenWeatherMaporg))
#data_accuweather = pd.read_sql('SELECT dimension FROM accuweathercom', con = fl.getConnectionAccuweathercom))
dataList.append(dwd_se.execute('SELECT average_temp FROM dwd'))
sample_query = dwd_se.execute('SELECT average_temp FROM dwd')
FunctionLibraryExtended.getResult(sample_query, dwd_se)
# dataList.append(pd.read_sql('SELECT average_temp FROM dwd', con = fl.getConnectionDWD()))
# dataList.append(pd.read_sql('SELECT maxTemp FROM getConnectionWetterdienstde', con = fl.getConnectionWetterdienstde()))
# dataList.append(pd.read_sql('SELECT maxTemp+minTemp FROM wetterde', con = fl.getConnectionWetterde()))
# dataList.append(pd.read_sql('SELECT (maxTemp+minTemp)/2 FROM wettercom', con = fl.getConnectionWettercom()))
# dataList.append(pd.read_sql('SELECT (maxTemp+minTemp)/2 FROM openweathermaporg', con = fl.getConnectionOpenWeatherMaporg()))
# dataList.append(pd.read_sql('SELECT (maxTemp+minTemp)/2 FROM accuweathercom', con = fl.getConnectionAccuweathercom()))
fig = plt.figure(figsize = (5,8))
for data in dataList:
data.plot(kind = 'box')
fig.add_subplot(111)
df.data.plot()
#ax = fig.add_subplot(111)
#bp = ax.boxplot(dataPlot)
#ax.set_xticklabels(labels)
fig.show()
plt.show()
import pandas as pd import scipy as sc from scipy import stats import FunctionLibraryExtended as fle import MySql from sqlalchemy import create_engine import FunctionLibraryExtended as fle import sqlalchemy as sqla from sqlalchemy import * from sqlalchemy.ext.declarative import declarative_base import numpy as np import matplotlib import matplotlib.pyplot as plt dwd, se1 = fle.getConnectionDWD() acc, se2 = fle.getConnectionAccuweathercom() openW, se3 = fle.getConnectionOpenWeatherMaporg() wetter_com, se4 = fle.getConnectionWettercom() wetter_de, se5 = fle.getConnectionWetterde() wetter_dienst, se6 = fle.getConnectionWetterdienstde() """ Queries: 1. Min_Temp 2. Max_Temp 3. Clouds 4. Wind_Speed 5. Precipitation Functions: 1. Difference 2. RMSE