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This chapter describes some of the data acquisition mode in the subset of pandas

14 Select a subset of data

14.1 Select the row of Series

14.1.1 Get a column from the DataFrame as Series

city = college_data["CITY"]
print(city)
print("<"+"="*75+">")
print("类型为：",type(city))

INSTNM
Alabama A & M University                                            Normal
University of Alabama at Birmingham                             Birmingham
Amridge University                                              Montgomery
University of Alabama in Huntsville                             Huntsville
                                                                ...       
Rasmussen College - Overland Park                            Overland Park
National Personal Training Institute of Cleveland         Highland Heights
Bay Area Medical Academy - San Jose Satellite Location            San Jose
Excel Learning Center-San Antonio South                        San Antonio
Name: CITY, Length: 7535, dtype: object
<===========================================================================>
类型为： <class 'pandas.core.series.Series'>

14.1.2 iloc usage

14.1.2.1 Select an incoming integer index

city.iloc[0]

'Normal'

14.1.2.2 Incoming integer list to select a new Series

# 当传入列表时发现获取出来的数据结构依然是一个Series
city.iloc[[0,1,2,3]]

INSTNM
Alabama A & M University                   Normal
University of Alabama at Birmingham    Birmingham
Amridge University                     Montgomery
University of Alabama in Huntsville    Huntsville
Name: CITY, dtype: object

14.1.2.3 Shard acquisition

# 获取整数索引 [0,10) 步长为2,这样选出的依然为Series
city[0:10:2]

INSTNM
Alabama A & M University                     Normal
Amridge University                       Montgomery
Alabama State University                 Montgomery
Central Alabama Community College    Alexander City
Auburn University at Montgomery          Montgomery
Name: CITY, dtype: object

14.1.3 loc usage

Pass in an index to select one

city["Alabama A & M University"]

'Normal'

14.1.3.1 Select multiple lines from the tag list

# 这样通过传入的标签索引列表选取多行,返回的依然是Series
city[["Alabama A & M University","Amridge University"]]

INSTNM
Alabama A & M University        Normal
Amridge University          Montgomery
Name: CITY, dtype: object

14.1.3.2 Shard selection

# 选取标签索引 [start_target,end_target] 步长为1的行,返回的是Series,注意这里是端点值都能取到
city["Alabama A & M University":"University of Alabama in Huntsville":1]

INSTNM
Alabama A & M University                   Normal
University of Alabama at Birmingham    Birmingham
Amridge University                     Montgomery
University of Alabama in Huntsville    Huntsville
Name: CITY, dtype: object

14.2 Select rows of DataFrame

14.2.1 iloc usage

14.2.1.1 Pass in an integer index value to get a row of data (return type is Series)

college_data.iloc[0]

CITY                  Normal
STABBR                    AL
HBCU                       1
MENONLY                    0
                       ...  
PCTFLOAN              0.8284
UG25ABV               0.1049
MD_EARN_WNE_P10        30300
GRAD_DEBT_MDN_SUPP     33888
Name: Alabama A & M University, Length: 26, dtype: object

14.2.1.2 Pass in an integer index list and return multiple rows of data of type (DataFrame)

college_data.iloc[[1,3,5,7,9]]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
University of Alabama at Birmingham	Birmingham	AL	0.0	0.0	...	0.5214	0.2422	39700	21941.5
University of Alabama in Huntsville	Huntsville	AL	0.0	0.0	...	0.4596	0.2640	45500	24097
The University of Alabama	Tuscaloosa	AL	0.0	0.0	...	0.4010	0.0853	41900	23750
Athens State University	Athens	AL	0.0	0.0	...	0.6296	0.6410	39000	18595
Auburn University	Auburn	AL	0.0	0.0	...	0.3494	0.0415	45700	21831

5 rows × 26 columns

14.2.1.3 Shard Acquisition

# 获取索引为 [1,10) 步长为2 中的数据行,返回为DataFrame
college_data.iloc[1:10:2]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
University of Alabama at Birmingham	Birmingham	AL	0.0	0.0	...	0.5214	0.2422	39700	21941.5
University of Alabama in Huntsville	Huntsville	AL	0.0	0.0	...	0.4596	0.2640	45500	24097
The University of Alabama	Tuscaloosa	AL	0.0	0.0	...	0.4010	0.0853	41900	23750
Athens State University	Athens	AL	0.0	0.0	...	0.6296	0.6410	39000	18595
Auburn University	Auburn	AL	0.0	0.0	...	0.3494	0.0415	45700	21831

5 rows × 26 columns

14.2.2 loc usage

14.2.2.1 Passing a label to get a row

# 获取标签索引对应的数据行,返回类型为Series
college_data.loc["University of Alabama at Birmingham"]

CITY                  Birmingham
STABBR                        AL
HBCU                           0
MENONLY                        0
                         ...    
PCTFLOAN                  0.5214
UG25ABV                   0.2422
MD_EARN_WNE_P10            39700
GRAD_DEBT_MDN_SUPP       21941.5
Name: University of Alabama at Birmingham, Length: 26, dtype: object

14.2.2.2 传入一个标签列表获取多行

# 根据传入的标签列表返回相应的数据行,返回类型为DataFrame
college_data.loc[["University of Alabama at Birmingham","The University of Alabama"]]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
University of Alabama at Birmingham	Birmingham	AL	0.0	0.0	...	0.5214	0.2422	39700	21941.5
The University of Alabama	Tuscaloosa	AL	0.0	0.0	...	0.4010	0.0853	41900	23750

2 rows × 26 columns

14.2.2.3 分片获取

# 获取[start_target,end_tartget] 步长为 1 的数据行,返回为DataFrame
college_data.loc["University of Alabama at Birmingham":"University of Alabama in Huntsville":1]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
University of Alabama at Birmingham	Birmingham	AL	0.0	0.0	...	0.5214	0.2422	39700	21941.5
Amridge University	Montgomery	AL	0.0	0.0	...	0.7795	0.8540	40100	23370
University of Alabama in Huntsville	Huntsville	AL	0.0	0.0	...	0.4596	0.2640	45500	24097

3 rows × 26 columns

14.3 同时选取DataFrame的行和列

14.3.1 获取前n行m列

14.3.1.1 用 iloc 方法实现

# 获取前面两行三列数据
college_data.iloc[:2,:3]

	CITY	STABBR	HBCU
INSTNM
Alabama A & M University	Normal	AL	1.0
University of Alabama at Birmingham	Birmingham	AL	0.0

14.3.1.2 用 loc方法实现

# 获取行索引从[start_target,end_target]的行,和列索引为[start,end]的列
college_data.loc[:"University of Alabama at Birmingham",:"HBCU"]

	CITY	STABBR	HBCU
INSTNM
Alabama A & M University	Normal	AL	1.0
University of Alabama at Birmingham	Birmingham	AL	0.0

14.3.2 获取全部行中的前n列

14.3.2.1 用 iloc 方法实现

college_data.iloc[:,:2]

	CITY	STABBR
INSTNM
Alabama A & M University	Normal	AL
University of Alabama at Birmingham	Birmingham	AL
Amridge University	Montgomery	AL
University of Alabama in Huntsville	Huntsville	AL
...	...	...
Rasmussen College - Overland Park	Overland Park	KS
National Personal Training Institute of Cleveland	Highland Heights	OH
Bay Area Medical Academy - San Jose Satellite Location	San Jose	CA
Excel Learning Center-San Antonio South	San Antonio	TX

7535 rows × 2 columns

14.3.2.2 用 loc 方法实现

college_data.loc[:,:"STABBR"]

	CITY	STABBR
INSTNM
Alabama A & M University	Normal	AL
University of Alabama at Birmingham	Birmingham	AL
Amridge University	Montgomery	AL
University of Alabama in Huntsville	Huntsville	AL
...	...	...
Rasmussen College - Overland Park	Overland Park	KS
National Personal Training Institute of Cleveland	Highland Heights	OH
Bay Area Medical Academy - San Jose Satellite Location	San Jose	CA
Excel Learning Center-San Antonio South	San Antonio	TX

7535 rows × 2 columns

14.3.3 选取不连续的行和列

14.3.3.1 用 iloc 方法实现

college_data.iloc[[1,3,5,7],[2,4,6,8]]

	HBCU	WOMENONLY	SATVRMID	DISTANCEONLY
INSTNM
University of Alabama at Birmingham	0.0	0.0	570.0	0.0
University of Alabama in Huntsville	0.0	0.0	595.0	0.0
The University of Alabama	0.0	0.0	555.0	0.0
Athens State University	0.0	0.0	NaN	0.0

14.3.3.2 用 loc 方法实现

# 这里实现的需求同上
college_data.loc[["University of Alabama at Birmingham","University of Alabama in Huntsville","The University of Alabama","Athens State University"],
                ["HBCU","WOMENONLY","SATVRMID","DISTANCEONLY"]]

	HBCU	WOMENONLY	SATVRMID	DISTANCEONLY
INSTNM
University of Alabama at Birmingham	0.0	0.0	570.0	0.0
University of Alabama in Huntsville	0.0	0.0	595.0	0.0
The University of Alabama	0.0	0.0	555.0	0.0
Athens State University	0.0	0.0	NaN	0.0

14.3.4 选取某一个标量的值

14.3.4.1 用 iloc方法实现

# 选取第四行四列的值
college_data.iloc[3,3]

0.0

14.3.4.2 用 loc 方法实现

# 实现的需求同上
college_data.loc["Athens State University","MENONLY"]

0.0

14.3.4.3 使用 iat 快速获取标量

%timeit college_data.iloc[1000,3]
# 可以看到使用iat方法,时间上大概节约了一半
%timeit college_data.iat[1000,3]

7.95 µs ± 691 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
4.74 µs ± 21.5 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

14.3.4.4 使用at快速获取标量

%timeit college_data.loc["Rasmussen College - Overland Park","CITY"]
# 同样发现使用at方法比loc的速度也快
%timeit college_data.at["Rasmussen College - Overland Park","CITY"]

6.41 µs ± 58.4 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
4.16 µs ± 20.5 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

14.4 补充

14.4.1 惰性切片

# 同样试用于Series
college_data[2:10:2]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
Amridge University	Montgomery	AL	0.0	0.0	...	0.7795	0.8540	40100	23370
Alabama State University	Montgomery	AL	1.0	0.0	...	0.7554	0.1270	26600	33118.5
Central Alabama Community College	Alexander City	AL	0.0	0.0	...	0.3977	0.3153	27500	16127
Auburn University at Montgomery	Montgomery	AL	0.0	0.0	...	0.5803	0.2930	35000	21335

4 rows × 26 columns

# 利用标签索引获取
college_data[:"Central Alabama Community College"]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
Alabama A & M University	Normal	AL	1.0	0.0	...	0.8284	0.1049	30300	33888
University of Alabama at Birmingham	Birmingham	AL	0.0	0.0	...	0.5214	0.2422	39700	21941.5
Amridge University	Montgomery	AL	0.0	0.0	...	0.7795	0.8540	40100	23370
University of Alabama in Huntsville	Huntsville	AL	0.0	0.0	...	0.4596	0.2640	45500	24097
Alabama State University	Montgomery	AL	1.0	0.0	...	0.7554	0.1270	26600	33118.5
The University of Alabama	Tuscaloosa	AL	0.0	0.0	...	0.4010	0.0853	41900	23750
Central Alabama Community College	Alexander City	AL	0.0	0.0	...	0.3977	0.3153	27500	16127

7 rows × 26 columns

14.4.2 按照字母分片

# 按照字母分片必须先对标签索引进行排序
college_data.sort_index(ascending=True)["A":"E"]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
A & W Healthcare Educators	New Orleans	LA	0.0	0.0	...	0.8596	0.6667	NaN	19022.5
A T Still University of Health Sciences	Kirksville	MO	0.0	0.0	...	NaN	NaN	219800	PrivacySuppressed
ABC Beauty Academy	Garland	TX	0.0	0.0	...	0.0000	0.8286	NaN	PrivacySuppressed
ABC Beauty College Inc	Arkadelphia	AR	0.0	0.0	...	1.0000	0.4688	PrivacySuppressed	16500
...	...	...	...	...	...	...	...	...	...
Durham Technical Community College	Durham	NC	0.0	0.0	...	0.1796	0.5961	27200	11069.5
Dutchess BOCES-Practical Nursing Program	Poughkeepsie	NY	0.0	0.0	...	0.6275	0.5430	36500	9500
Dutchess Community College	Poughkeepsie	NY	0.0	0.0	...	0.1936	0.1806	32500	10250
Dyersburg State Community College	Dyersburg	TN	0.0	0.0	...	0.2493	0.3097	26800	7475

1900 rows × 26 columns

# 当然还可以反向获取
college_data.sort_index()["E":"F"]

	CITY	STABBR	HBCU	MENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
INSTNM
E Q School of Hair Design	Council Bluffs	IA	0.0	0.0	...	0.6737	0.1471	18100	7830
ECPI University	Virginia Beach	VA	0.0	0.0	...	0.5001	0.6633	37000	20000
ECPI University-Charleston	North Charleston	SC	NaN	NaN	...	NaN	NaN	NaN	20000
ECPI University-Charlotte	Charlotte	NC	NaN	NaN	...	NaN	NaN	NaN	20000
...	...	...	...	...	...	...	...	...	...
Excelsior College	Albany	NY	0.0	0.0	...	0.0800	0.9337	PrivacySuppressed	11010
Expertise Cosmetology Institute	Las Vegas	NV	0.0	0.0	...	1.0000	0.4828	PrivacySuppressed	8450
Exposito School of Hair Design	Amarillo	TX	0.0	0.0	...	0.6267	0.3966	15100	PrivacySuppressed
Expression College for Digital Arts	Emeryville	CA	0.0	0.0	...	0.7736	0.3955	PrivacySuppressed	35662

381 rows × 26 columns

14.4.3 更换索引

college_data.set_index("CITY")

	STABBR	HBCU	MENONLY	WOMENONLY	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
CITY
Normal	AL	1.0	0.0	0.0	...	0.8284	0.1049	30300	33888
Birmingham	AL	0.0	0.0	0.0	...	0.5214	0.2422	39700	21941.5
Montgomery	AL	0.0	0.0	0.0	...	0.7795	0.8540	40100	23370
Huntsville	AL	0.0	0.0	0.0	...	0.4596	0.2640	45500	24097
...	...	...	...	...	...	...	...	...	...
Overland Park	KS	NaN	NaN	NaN	...	NaN	NaN	NaN	21163
Highland Heights	OH	NaN	NaN	NaN	...	NaN	NaN	NaN	6333
San Jose	CA	NaN	NaN	NaN	...	NaN	NaN	NaN	PrivacySuppressed
San Antonio	TX	NaN	NaN	NaN	...	NaN	NaN	NaN	12125

7535 rows × 25 columns

14.4.4 复原索引

college_data.reset_index()

	INSTNM	CITY	STABBR	HBCU	...	PCTFLOAN	UG25ABV	MD_EARN_WNE_P10	GRAD_DEBT_MDN_SUPP
0	Alabama A & M University	Normal	AL	1.0	...	0.8284	0.1049	30300	33888
1	University of Alabama at Birmingham	Birmingham	AL	0.0	...	0.5214	0.2422	39700	21941.5
2	Amridge University	Montgomery	AL	0.0	...	0.7795	0.8540	40100	23370
3	University of Alabama in Huntsville	Huntsville	AL	0.0	...	0.4596	0.2640	45500	24097
...	...	...	...	...	...	...	...	...	...
7531	Rasmussen College - Overland Park	Overland Park	KS	NaN	...	NaN	NaN	NaN	21163
7532	National Personal Training Institute of Cleveland	Highland Heights	OH	NaN	...	NaN	NaN	NaN	6333
7533	Bay Area Medical Academy - San Jose Satellite ...	San Jose	CA	NaN	...	NaN	NaN	NaN	PrivacySuppressed
7534	Excel Learning Center-San Antonio South	San Antonio	TX	NaN	...	NaN	NaN	NaN	12125

7535 rows × 27 columns

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