I want to get net income and research development for the current year from multiple companies. At present, ticker.financials from yfinance library gives me the full table for 4 years and for multiple metrics.

I am checking below the keys for financials and there are only by years.

# Import packages
import yfinance as yf
import pandas as pd

msft = yf.Ticker("MSFT")
info = msft.financials
info.keys()

DatetimeIndex(['2021-06-30', '2020-06-30', '2019-06-30', '2018-06-30'], dtype='datetime64[ns]', name='', freq=None)

For example,

msft.financials

gives me this

I want to create a ticker group like

tickers = ["AAPL", "MSFT", "IBM", "GOOG", "ORCL"]

For these companies I need the net income and research and development for 2021-06-30.

How is this possible with yfinance?

CodePudding user response：

Since the format in which the company's financial information is obtained is a data frame, the latest closing date is combined into an empty data frame. After merging, update the column names in the ticker list. The following is a part of the dataframe after the retrieval. With the obtained data, we extract the necessary subjects for each.

import yfinance as yf
import pandas as pd

tickers = ["AAPL", "MSFT", "IBM", "GOOG", "ORCL"]

df = pd.DataFrame()
cols = []
for ticker in tickers:
    company = yf.Ticker(ticker)
    info = company.financials
    df = pd.concat([df, info.iloc[:,0]], axis=1)
    cols.append(ticker '(' info.columns[0].strftime('%Y-%m-%d') ')')
df.columns = cols

df.head()

    AAPL(2021-09-25)    MSFT(2021-06-30)    IBM(2020-12-31)     GOOG(2020-12-31)    ORCL(2021-05-31)
Research Development    21914000000.0   20716000000.0   6333000000.0    27573000000.0   6527000000.0
Effect Of Accounting Charges    None    None    None    None    None
Income Before Tax   109207000000.0  71102000000.0   4637000000.0    48082000000.0   12999000000.0
Minority Interest   None    None    129000000.0     None    714000000.0
Net Income  94680000000.0   61271000000.0   5590000000.0    40269000000.0   13746000000.0

Research Development & Income

df.iloc[[0,4],]