A handy tool to get nasdaq data in python
Project description
Install guide
pip install nasdaq-data
How to
First import and create an instance of your nasdaq data grabber object
from nasdaq_data import nasdaq_grabber as ng
my_ng = ng()
Get Top Stocks by Market Cap
Call nasdaq_stocks and input the number of tickers you want and you will get info on stocks in order of Market Cap
my_ng.nasdaq_stocks(10)
symbol | name | lastsale | netchange | pctchange | marketCap | url | |
---|---|---|---|---|---|---|---|
0 | AAPL | Apple Inc. Common Stock | $150.43 | -2.31 | -1.512% | 2,608,056,056,200 | /market-activity/stocks/aapl |
1 | MSFT | Microsoft Corporation Common Stock | $237.92 | -3.06 | -1.27% | 1,774,381,634,186 | /market-activity/stocks/msft |
2 | GOOG | Alphabet Inc. Class C Capital Stock | $99.17 | -1.40 | -1.392% | 1,293,573,480,000 | /market-activity/stocks/goog |
3 | GOOGL | Alphabet Inc. Class A Common Stock | $98.74 | -1.40 | -1.398% | 1,287,964,560,000 | /market-activity/stocks/googl |
4 | AMZN | Amazon.com, Inc. Common Stock | $113.78 | -3.53 | -3.009% | 1,157,926,339,396 | /market-activity/stocks/amzn |
5 | TSLA | Tesla, Inc. Common Stock | $275.33 | -13.26 | -4.595% | 862,738,307,490 | /market-activity/stocks/tsla |
6 | BRK/A | Berkshire Hathaway Inc. | $404485.25 | -889.76 | -0.219% | 594,946,837,609 | /market-activity/stocks/brk/a |
7 | BRK/B | Berkshire Hathaway Inc. | $267.77 | -0.74 | -0.276% | 590,783,995,813 | /market-activity/stocks/brk/b |
8 | UNH | UnitedHealth Group Incorporated Common Stock (DE) | $513.61 | -3.85 | -0.744% | 480,421,913,683 | /market-activity/stocks/unh |
9 | JNJ | Johnson & Johnson Common Stock | $166.72 | 0.54 | 0.325% | 438,336,872,094 | /market-activity/stocks/jnj |
Get Historical Prices
Pass a start date and end date in ISO format along with your ticker to nasdaq_historical_price to get historical prices
from dateutil.relativedelta import relativedelta
import time
import datetime as dt
#today
t = dt.date.today().replace(day=1)
#one year ago
t0 = t - relativedelta(years=1)
#isoformat
iso_t0, iso_t = t0.isoformat(), t.isoformat()
my_ng.nasdaq_historical_price('AAPL', iso_t0, iso_t)
date | close | volume | open | high | low | |
---|---|---|---|---|---|---|
0 | 09/01/2022 | $157.96 | 74,229,900 | $156.64 | $158.42 | $154.67 |
1 | 08/31/2022 | $157.22 | 87,991,090 | $160.305 | $160.58 | $157.14 |
2 | 08/30/2022 | $158.91 | 77,906,200 | $162.13 | $162.56 | $157.72 |
3 | 08/29/2022 | $161.38 | 73,313,950 | $161.145 | $162.9 | $159.82 |
4 | 08/26/2022 | $163.62 | 78,960,980 | $170.57 | $171.05 | $163.56 |
... | ... | ... | ... | ... | ... | ... |
248 | 09/08/2021 | $155.11 | 74,420,210 | $156.98 | $157.04 | $153.975 |
249 | 09/07/2021 | $156.69 | 82,278,260 | $154.97 | $157.26 | $154.39 |
250 | 09/03/2021 | $154.3 | 57,866,070 | $153.76 | $154.63 | $153.09 |
251 | 09/02/2021 | $153.65 | 71,171,320 | $153.87 | $154.72 | $152.4 |
252 | 09/01/2021 | $152.51 | 80,313,710 | $152.83 | $154.98 | $152.34 |
253 rows × 6 columns
Get Stocks Financal Data
Call nasdaq_financals and pass in a frequency you desire
- Annual
- Semi Annual
my_ng.nasdaq_financals('AAPL', 1)
symbol | tabs.incomeStatementTable | tabs.balanceSheetTable | tabs.cashFlowTable | tabs.financialRatiosTable | incomeStatementTable.headers.value1 | incomeStatementTable.headers.value2 | incomeStatementTable.headers.value3 | incomeStatementTable.headers.value4 | incomeStatementTable.headers.value5 | ... | cashFlowTable.headers.value3 | cashFlowTable.headers.value4 | cashFlowTable.headers.value5 | cashFlowTable.rows | financialRatiosTable.headers.value1 | financialRatiosTable.headers.value2 | financialRatiosTable.headers.value3 | financialRatiosTable.headers.value4 | financialRatiosTable.headers.value5 | financialRatiosTable.rows | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | AAPL | Income Statement | Balance Sheet | Cash Flow | Financial Ratios | Period Ending: | 9/25/2021 | 9/26/2020 | 9/28/2019 | 9/29/2018 | ... | 9/26/2020 | 9/28/2019 | 9/29/2018 | [{'value1': 'Net Income', 'value2': '$94,680,0... | Period Ending: | 9/25/2021 | 9/26/2020 | 9/28/2019 | 9/29/2018 | [{'value1': 'Liquidity Ratios', 'value2': '', ... |
1 rows × 29 columns
Get Other Data
Calling the nasdaq_data function and supplying type to any of the numbers below will get you
- Analyst Target Price and Ratings
- PEG Ratio
- Momentum Estimate
- Earnings Forecast
- Earnings Surprise
- EPS
#analysts ratings
my_ng.nasdaq_data('AAPL',1)
symbol | historicalConsensus | consensusOverview.lowPriceTarget | consensusOverview.highPriceTarget | consensusOverview.priceTarget | consensusOverview.buy | consensusOverview.sell | consensusOverview.hold | |
---|---|---|---|---|---|---|---|---|
0 | aapl | [{'z': {'buy': 19, 'hold': 5, 'sell': 0, 'date... | 136.0 | 220.0 | 183.45 | 23 | 1 | 4 |
#PEG Ratio
my_ng.nasdaq_data('AAPL',2)
pegr.label | pegr.text | pegr.pegValue | per.peRatioChart | per.label | per.text | per.dataProvider | gr.peGrowthChart | gr.title | |
---|---|---|---|---|---|---|---|---|---|
0 | Forecast 12 Month Forward PEG Ratio | Investors are always looking for companies wit... | 1.95 | [{'x': '2021 Actual', 'y': 26.81}, {'x': '2022... | Price/Earnings Ratio | Price/Earnings Ratio is a widely used stock ev... | <b>Data Provider:</b> Zacks Investment Research | [{'z': 'Growth', 'x': '2022', 'y': 8.8}, {'z':... | Forecast P/E Growth Rates |
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