QUANTAXIS的高级财务获取方法

1.QA.QA_fetch_financial_report(code,report_date)

其中, report_date 是需要手动指定的财务时间, 可以是单个时间,也可以是一列时间:

'2018-03-31' 或者['2017-03-31','2017-06-30','2017-09-31','2017-12-31','2018-03-31'] 此方法的意义在于指定特定的财务时间(如年报)

返回的是一个MultiIndex的dataframe

2.QA.QA_fetch_financial_report_adv(code,start,end)

支持随意的跨时间索引, start 和end不用刻意指定

如果end不写,则start参数等同于report_date的用法

返回的是QA_DataStruct_Financial 类

  1. QA_DataStruct_Financial 类, 可以直接加载在基础方法返回的dataframe中

QDF.get_report_by_date(code,date) 返回某个股票的某个时间点的财报

QDF.get_key(code,date,key) 返回某个股票某个时间点的财报的某个指标

import QUANTAXIS as QA
import pandas as pd
res=QA.QA_fetch_financial_report(['000001','600100'],['2017-03-31','2017-06-30','2017-09-31','2017-12-31','2018-03-31'])
res

EPS

deductEPS

undistributedProfitPerShare

netAssetsPerShare

capitalReservePerShare

ROE

operatingCashFlowPerShare

moneyFunds

tradingFinancialAssets

billsReceivables

...

netProfitLastYear

277

278

279

280

281

282

_id

code

report_date

report_date

code

2017-03-31

000001

0.3100

0.3100

4.05

10.9400

3.29

2.992

-6.700

7.121477e+11

4.404400e+10

NaN

...

2.272700e+10

NaN

NaN

2.0

6.955837e+08

2.89

0.3617

5b3edccc50d2c15048795415

000001

2017-03-31

2017-06-30

000001

0.6800

0.6800

4.26

11.1500

3.29

6.100

-7.470

7.522773e+11

4.908300e+10

NaN

...

2.286100e+10

NaN

NaN

2.0

7.684470e+08

6.21

0.3670

5b3edcce50d2c15048796114

000001

2017-06-30

2017-12-31

000001

1.3000

1.3000

4.64

11.7706

3.29

11.474

-6.920

7.506320e+11

3.957500e+10

NaN

...

2.318900e+10

NaN

NaN

3.0

1.071157e+09

11.62

0.2348

5b3edcd150d2c15048797c47

000001

2017-12-31

2018-03-31

000001

0.3300

0.3300

4.69

11.8500

3.29

3.242

2.410

6.699981e+11

7.684500e+10

NaN

...

2.357000e+10

NaN

NaN

3.0

9.828775e+08

2.79

0.3818

5b3edcd250d2c15048798a07

000001

2018-03-31

2017-03-31

600100

-0.0908

-0.1030

2.57

7.1879

3.15

-1.263

-0.885

7.738101e+09

9.173491e+08

90043088.0

...

-1.169131e+09

NaN

NaN

3.0

4.155126e+07

-1.25

-0.1030

5b3edccc50d2c15048795c3a

600100

2017-03-31

2017-06-30

600100

-0.0407

-0.0598

2.37

6.9775

3.15

-0.584

-1.124

8.756578e+09

7.745308e+08

52524456.0

...

-7.752181e+08

NaN

NaN

3.0

4.842445e+07

-0.56

0.0432

5b3edcce50d2c15048796987

600100

2017-06-30

2017-12-31

600100

0.0350

-0.0115

2.45

7.1765

3.10

0.487

0.153

9.766134e+09

5.818680e+08

117617800.0

...

1.036393e+08

NaN

NaN

4.0

5.628596e+07

0.48

0.0791

5b3edcd150d2c150487984ca

600100

2017-12-31

2018-03-31

600100

-0.0756

-0.0871

2.37

7.1433

3.20

-1.058

-0.757

7.666613e+09

5.546273e+08

97230120.0

...

1.487741e+08

NaN

NaN

2.0

4.165037e+07

-1.06

-0.0871

5b3edcd250d2c15048799289

600100

2018-03-31

8 rows × 285 columns

res_adv=QA.QA_fetch_financial_report_adv('000001','2017-01-01','2018-05-01')
res_adv
< QA_DataStruct_Financial >
res_adv.data

EPS

deductEPS

undistributedProfitPerShare

netAssetsPerShare

capitalReservePerShare

ROE

operatingCashFlowPerShare

moneyFunds

tradingFinancialAssets

billsReceivables

...

netProfitLastYear

277

278

279

280

281

282

_id

code

report_date

report_date

code

2017-03-31

000001

0.31

0.31

4.05

10.9400

3.29

2.992

-6.70

7.121477e+11

4.404400e+10

NaN

...

2.272700e+10

NaN

NaN

2.0

6.955837e+08

2.89

0.3617

5b3edccc50d2c15048795415

000001

2017-03-31

2017-06-30

000001

0.68

0.68

4.26

11.1500

3.29

6.100

-7.47

7.522773e+11

4.908300e+10

NaN

...

2.286100e+10

NaN

NaN

2.0

7.684470e+08

6.21

0.3670

5b3edcce50d2c15048796114

000001

2017-06-30

2017-09-30

000001

1.06

1.06

4.64

11.5400

3.29

8.782

-9.20

7.265024e+11

4.132700e+10

NaN

...

2.303300e+10

NaN

NaN

3.0

8.339691e+08

9.60

0.3854

5b3edccf50d2c15048796eaa

000001

2017-09-30

2017-12-31

000001

1.30

1.30

4.64

11.7706

3.29

11.474

-6.92

7.506320e+11

3.957500e+10

NaN

...

2.318900e+10

NaN

NaN

3.0

1.071157e+09

11.62

0.2348

5b3edcd150d2c15048797c47

000001

2017-12-31

2018-03-31

000001

0.33

0.33

4.69

11.8500

3.29

3.242

2.41

6.699981e+11

7.684500e+10

NaN

...

2.357000e+10

NaN

NaN

3.0

9.828775e+08

2.79

0.3818

5b3edcd250d2c15048798a07

000001

2018-03-31

5 rows × 285 columns

fds=QA.QA_DataStruct_Financial(res)
fds
< QA_DataStruct_Financial >
fds.get_key('600100','2017-03-31','ROE')
-1.2630000114
fds.get_report_by_date('600100','2017-03-31')
EPS -0.0908
deductEPS -0.103
undistributedProfitPerShare 2.57
netAssetsPerShare 7.1879
capitalReservePerShare 3.15
ROE -1.263
operatingCashFlowPerShare -0.885
moneyFunds 7.7381e+09
tradingFinancialAssets 9.17349e+08
billsReceivables 9.00431e+07
accountsReceivables 7.19131e+09
prepayments 1.51541e+09
otherReceivables 9.41644e+08
interCompanyReceivables NaN
interestReceivables 0
dividendsReceivables 1.68134e+07
inventory 9.57452e+09
expendableBiologicalAssets NaN
noncurrentAssetsDueWithinOneYear 0
otherLiquidAssets 3.17298e+09
totalLiquidAssets 3.11582e+10
availableForSaleSecurities 2.92698e+09
heldToMaturityInvestments 0
longTermReceivables 8.95877e+08
longTermEquityInvestment 1.33009e+10
investmentRealEstate 1.45896e+07
fixedAssets 3.26195e+09
constructionInProgress 6.67087e+08
engineerMaterial 0
fixedAssetsCleanUp 0
...
socialSecurityNumber NaN
socialSecurityShareholding NaN
privateEquityNumber 1
privateEquityShareholding 8.00007e+06
financialCompanyNumber NaN
financialCompanyShareholding NaN
pensionInsuranceAgencyNumber NaN
pensionInsuranceAgencyShareholfing NaN
totalNumberOfTopTenCirculationShareholders 5.85248e+08
firstLargeCirculationShareholdersNumber 4.73639e+08
freeCirculationStock 1.72424e+09
limitedCirculationAShares 7.66017e+08
generalRiskPreparation NaN
otherComprehensiveIncome -2.10654e+08
totalComprehensiveIncome -5.05396e+08
shareholdersOwnershipOfAParentCompany 2.13041e+10
bankInstutionNumber NaN
bankInstutionShareholding NaN
corporationNumber 1
corporationShareholding 4.73639e+08
netProfitLastYear -1.16913e+09
277 NaN
278 NaN
279 3
280 4.15513e+07
281 -1.25
282 -0.103
_id 5b3edccc50d2c15048795c3a
code 600100
report_date 2017-03-31 00:00:00
Name: (2017-03-31 00:00:00, 600100), Length: 285, dtype: object