Last update: 04.02.2019 15:59:26 # Sample code generated by DasData www.DasData.co import requests import pandas as pd import matplotlib.pyplot as plt plt.style.use('seaborn-whitegrid') import numpy as np %matplotlib inline data_url = 'https://DasData.co/e.aspx?das=gcFJZnSRPBlZrDB59rrmZde1W7rdjgEngfyTiuI50HnsQ2hUFyzP7qUppGhXYq/CIdvrje6ZsvtWsJ5y9ObRoA==&from=0&to=500&json=1' response = requests.get(data_url, data={"limit" : "500"}) if response.status_code == 200: df = pd.DataFrame.from_records(response.json()) print(df) #==================================================================== df[['id','AIDate','Water_soil','Umiditate_sol','Umiditate_sera','Temp_afara','Temp_sera','Temp_sol' ]] = df['Table'].apply(pd.Series) #==================================================================== df["AIDate"] = pd.to_datetime(df["AIDate"]) df.set_index('AIDate', inplace=True) df.head() Water_soil=df[['Water_soil']] Umiditate_sol=df[['Umiditate_sol']] Umiditate_sera=df[['Umiditate_sera']] Temp_afara=df[['Temp_afara']] Temp_sera=df[['Temp_sera']] Temp_sol=df[['Temp_sol']] #==================================================================== df_rm = pd.concat([Water_soil.rolling(12).mean(),Umiditate_sol.rolling(12).mean(),Umiditate_sera.rolling(12).mean(),Temp_afara.rolling(12).mean(),Temp_sera.rolling(12).mean(),Temp_sol.rolling(12).mean()], axis=1) #==================================================================== df_rm.plot(figsize=(20,10), linewidth=2, fontsize=15) x = np.linspace(0, 10, 50) plt.xlabel('AIDate', fontsize=12);