rogernogueira

lat,lng,desc,zip,title,timeStamp,twp,addr,e
40.2978759,-75.5812935,REINDEER CT & DEAD END;  NEW HANOVER; Station 332; 2015-12-10 @ 17:10:52;,19525,EMS: BACK PAINS/INJURY,2015-12-10 17:10:52,NEW HANOVER,REINDEER CT & DEAD END,1
40.2580614,-75.2646799,BRIAR PATH & WHITEMARSH LN;  HATFIELD TOWNSHIP; Station 345; 2015-12-10 @ 17:29:21;,19446,EMS: DIABETIC EMERGENCY,2015-12-10 17:29:21,HATFIELD TOWNSHIP,BRIAR PATH & WHITEMARSH LN,1
40.1211818,-75.3519752,HAWS AVE; NORRISTOWN; 2015-12-10 @ 14:39:21-Station:STA27;,19401,Fire: GAS-ODOR/LEAK,2015-12-10 14:39:21,NORRISTOWN,HAWS AVE,1
40.1161530,-75.3435130,AIRY ST & SWEDE ST;  NORRISTOWN; Station 308A; 2015-12-10 @ 16:47:36;,19401,EMS: CARDIAC EMERGENCY,2015-12-10 16:47:36,NORRISTOWN,AIRY ST & SWEDE ST,1
40.2514920,-75.6033497,CHERRYWOOD CT & DEAD END;  LOWER POTTSGROVE; Station 329; 2015-12-10 @ 16:56:52;,,EMS: DIZZINESS,2015-12-10 16:56:52,LOWER POTTSGROVE,CHERRYWOOD CT & DEAD END,1
40.2534732,-75.2832450,CANNON AVE & W 9TH ST;  LANSDALE; Station 345; 2015-12-10 @ 15

rogernogueira

import seaborn as sns
import matplotlib.pyplot  as plt
import pandas as pd
import numpy as np
import xlrd
df = pd.read_excel('Cenarius2017.xlsx')
df['ProcessosDistribuídos'] = df['ProcessosDistribuídos'].apply(lambda x: str(x).replace('.', ''))
df['ProcessosDistribuídos'] = df['ProcessosDistribuídos'].apply(lambda x: int(x))

df['ProcessosJulgados'] = df['ProcessosJulgados'].apply(lambda x: str(x).replace('.', ''))