Python pandas Group by

Ex
Group BY

step   1:df=pd.read_csv('ferrovial.csv')

df
step 2:data=df.groupby('city')
data
#aatlu lkheya pche output nai aave next line add karve

for city,city_df in data:

    print(city)

    print(city_df)

step 3:particular city joiti hoy to aa step add karvu

data.get_group("kerala")

Step 4:data.max() #max value aavse

step 5:data.mean()#mean value aavse

step 6:data.describe() # descibe lkheshu to mean,median,max,min bdhu j aavse

	Date	Close	High	Low	Open	Volume	city
0	02-01-2007	12.850	12.940	12.710	12.900	3080000.0	vado
1	03-01-2007	12.660	12.860	12.600	12.850	2740000.0	vado
2	04-01-2007	12.450	12.720	12.380	12.590	2330000.0	vado
3	05-01-2007	12.200	12.360	12.070	12.170	1930000.0	vado
4	08-01-2007	12.190	12.280	12.150	12.220	1970000.0	vado
5	09-01-2007	12.450	12.500	12.220	12.390	2560000.0	ahem
6	10-01-2007	12.280	12.480	12.260	12.400	2490000.0	ahem
7	11-01-2007	12.350	12.490	12.200	12.310	1760000.0	ahem
8	12-01-2007	12.500	12.530	12.310	12.590	1600000.0	kerala
9	15-01-2007	12.650	12.760	12.590	12.640	1310000.0	kerala
10	16-01-2007	12.430	12.740	12.360	12.560	1250000.0	surat