# yfinance

### Yahoo! Finance market data downloader

* <https://pypi.org/project/yfinance/>

### Quick Start

#### The Ticker module

The Ticker module, which allows you to access ticker data in a more Pythonic way:

Note: yahoo finance datetimes are received as UTC.

```python
pip install yfinance
```

```python
pip install yfinance --upgrade --no-cache-dir
```

```python
conda install -c ranaroussi yfinance
```

```python
import yfinance as yf

msft = yf.Ticker("MSFT")

# get stock info
msft.info

# get historical market data
hist = msft.history(period="max")

# show actions (dividends, splits)
msft.actions

# show dividends
msft.dividends

# show splits
msft.splits

# show financials
msft.financials
msft.quarterly_financials

# show major holders
msft.major_holders

# show institutional holders
msft.institutional_holders

# show balance sheet
msft.balance_sheet
msft.quarterly_balance_sheet

# show cashflow
msft.cashflow
msft.quarterly_cashflow

# show earnings
msft.earnings
msft.quarterly_earnings

# show sustainability
msft.sustainability

# show analysts recommendations
msft.recommendations

# show next event (earnings, etc)
msft.calendar

# show ISIN code - *experimental*
# ISIN = International Securities Identification Number
msft.isin

# show options expirations
msft.options

# get option chain for specific expiration
opt = msft.option_chain('YYYY-MM-DD')
# data available via: opt.calls, opt.puts
```

### To initialize multiple Ticker objects, use

```python
import yfinance as yf

tickers = yf.Tickers('msft aapl goog')
# ^ returns a named tuple of Ticker objects

# access each ticker using (example)
tickers.tickers.MSFT.info
tickers.tickers.AAPL.history(period="1mo")
tickers.tickers.GOOG.actions
```

#### Fetching data for multiple tickers

```python
import yfinance as yf
data = yf.download("SPY AAPL", start="2017-01-01", end="2017-04-30")
```

**added some options to make life easier**

```python
data = yf.download(  # or pdr.get_data_yahoo(...
        # tickers list or string as well
        tickers = "SPY AAPL MSFT",

        # use "period" instead of start/end
        # valid periods: 1d,5d,1mo,3mo,6mo,1y,2y,5y,10y,ytd,max
        # (optional, default is '1mo')
        period = "ytd",

        # fetch data by interval (including intraday if period < 60 days)
        # valid intervals: 1m,2m,5m,15m,30m,60m,90m,1h,1d,5d,1wk,1mo,3mo
        # (optional, default is '1d')
        interval = "1m",

        # group by ticker (to access via data['SPY'])
        # (optional, default is 'column')
        group_by = 'ticker',

        # adjust all OHLC automatically
        # (optional, default is False)
        auto_adjust = True,

        # download pre/post regular market hours data
        # (optional, default is False)
        prepost = True,

        # use threads for mass downloading? (True/False/Integer)
        # (optional, default is True)
        threads = True,

        # proxy URL scheme use use when downloading?
        # (optional, default is None)
        proxy = None
    )
```

### pandas\_datareader override

If your code uses pandas\_datareader and you want to download data faster, you can “hijack” pandas\_datareader.data.get\_data\_yahoo() method to use **yfinance** while making sure the returned data is in the same format as **pandas\_datareader**’s get\_data\_yahoo().

```python
from pandas_datareader import data as pdr

import yfinance as yf
yf.pdr_override() # <== that's all it takes :-)

# download dataframe
data = pdr.get_data_yahoo("SPY", start="2017-01-01", end="2017-04-30")
```

**Optional (if you want to use pandas\_datareader)**

* [pandas\_datareader](https://github.com/pydata/pandas-datareader) >= 0.4.0


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://yo-sarawut.gitbook.io/snippet/finance/library/yfinance.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.