
import pandas as pd


data = pd.read_csv("AAPL.csv", index_col=0, parse_dates=True)


data.head()


data['Daily chg'] = data['Close'] - data['Open']


data.head()


data['Normalized'] = data['Close'] / data['Close'].iloc[0]


data.head()


data.tail()


data['Close'].min()

56.092499


data.min()

Open          5.702000e+01
High          5.712500e+01
Low           5.315250e+01
Close         5.609250e+01
Adj Close     5.574422e+01
Volume        2.225040e+07
Daily chg    -6.870003e+00
Normalized    7.262340e-01
dtype: float64


data['Close'].argmin()

39


data.iloc[35:44]


data['Normalized'].min()

0.7262339772946828


data['Normalized'].argmin()

39


data['Close'].max()

142.919998


data['Close'].argmax()

251


data.iloc[251:]


data['Close'].mean()

98.8017784426877


data.head()


data.drop(labels=['High', 'Low', 'Adj Close', 'Volume'], axis=1, inplace=True)


data.head()

	Open	High	Low	Close	Adj Close	Volume
Date
2020-01-27	77.514999	77.942497	76.220001	77.237503	76.576187	161940000
2020-01-28	78.150002	79.599998	78.047501	79.422501	78.742477	162234000
2020-01-29	81.112503	81.962502	80.345001	81.084999	80.390747	216229200
2020-01-30	80.135002	81.022499	79.687500	80.967499	80.274246	126743200
2020-01-31	80.232498	80.669998	77.072502	77.377502	76.714989	199588400

	Open	High	Low	Close	Adj Close	Volume	Daily chg
Date
2020-01-27	77.514999	77.942497	76.220001	77.237503	76.576187	161940000	-0.277496
2020-01-28	78.150002	79.599998	78.047501	79.422501	78.742477	162234000	1.272499
2020-01-29	81.112503	81.962502	80.345001	81.084999	80.390747	216229200	-0.027504
2020-01-30	80.135002	81.022499	79.687500	80.967499	80.274246	126743200	0.832497
2020-01-31	80.232498	80.669998	77.072502	77.377502	76.714989	199588400	-2.854996

	Open	High	Low	Close	Adj Close	Volume	Daily chg	Normalized
Date
2020-01-27	77.514999	77.942497	76.220001	77.237503	76.576187	161940000	-0.277496	1.000000
2020-01-28	78.150002	79.599998	78.047501	79.422501	78.742477	162234000	1.272499	1.028289
2020-01-29	81.112503	81.962502	80.345001	81.084999	80.390747	216229200	-0.027504	1.049814
2020-01-30	80.135002	81.022499	79.687500	80.967499	80.274246	126743200	0.832497	1.048293
2020-01-31	80.232498	80.669998	77.072502	77.377502	76.714989	199588400	-2.854996	1.001813

	Open	High	Low	Close	Adj Close	Volume	Daily chg	Normalized
Date
2021-01-20	128.660004	132.490005	128.550003	132.029999	132.029999	104319500	3.369995	1.709403
2021-01-21	133.800003	139.669998	133.589996	136.869995	136.869995	120529500	3.069992	1.772067
2021-01-22	136.279999	139.850006	135.020004	139.070007	139.070007	114459400	2.790008	1.800550
2021-01-25	143.070007	145.089996	136.539993	142.919998	142.919998	157282400	-0.150009	1.850396
2021-01-26	143.600006	144.300003	141.369995	142.080002	142.080002	50388565	-1.520004	1.839521

	Open	High	Low	Close	Adj Close	Volume	Daily chg	Normalized
Date
2020-03-17	61.877499	64.402496	59.599998	63.215000	62.822491	324056000	1.337501	0.818450
2020-03-18	59.942501	62.500000	59.279999	61.667500	61.284599	300233600	1.724999	0.798414
2020-03-19	61.847500	63.209999	60.652500	61.195000	60.815033	271857200	-0.652500	0.792296
2020-03-20	61.794998	62.957500	57.000000	57.310001	56.954155	401693200	-4.484997	0.741997
2020-03-23	57.020000	57.125000	53.152500	56.092499	55.744217	336752800	-0.927501	0.726234
2020-03-24	59.090000	61.922501	58.575001	61.720001	61.336773	287531200	2.630001	0.799094
2020-03-25	62.687500	64.562500	61.075001	61.380001	60.998886	303602000	-1.307499	0.794692
2020-03-26	61.630001	64.669998	61.590000	64.610001	64.208832	252087200	2.980000	0.836511
2020-03-27	63.187500	63.967499	61.762501	61.935001	61.550438	204216800	-1.252499	0.801877

Modify DataFrames and Useful functions¶