import yfinance as yf
= "NVDA"
ticker = yf.download(ticker, start="2014-01-01", end="2024-01-01")
df df
[*********************100%***********************] 1 of 1 completed
Price | Adj Close | Close | High | Low | Open | Volume |
---|---|---|---|---|---|---|
Ticker | NVDA | NVDA | NVDA | NVDA | NVDA | NVDA |
Date | ||||||
2014-01-02 00:00:00+00:00 | 0.373992 | 0.396500 | 0.399500 | 0.393000 | 0.398000 | 260092000 |
2014-01-03 00:00:00+00:00 | 0.369512 | 0.391750 | 0.398000 | 0.390500 | 0.397250 | 259332000 |
2014-01-06 00:00:00+00:00 | 0.374464 | 0.397000 | 0.400000 | 0.392000 | 0.395750 | 409492000 |
2014-01-07 00:00:00+00:00 | 0.380594 | 0.403500 | 0.405000 | 0.398250 | 0.401000 | 333288000 |
2014-01-08 00:00:00+00:00 | 0.385782 | 0.409000 | 0.411000 | 0.403500 | 0.405000 | 308192000 |
... | ... | ... | ... | ... | ... | ... |
2023-12-22 00:00:00+00:00 | 48.819527 | 48.830002 | 49.382999 | 48.466999 | 49.195000 | 252507000 |
2023-12-26 00:00:00+00:00 | 49.268425 | 49.278999 | 49.599998 | 48.959999 | 48.967999 | 244200000 |
2023-12-27 00:00:00+00:00 | 49.406395 | 49.417000 | 49.680000 | 49.084999 | 49.511002 | 233648000 |
2023-12-28 00:00:00+00:00 | 49.511375 | 49.521999 | 49.883999 | 49.411999 | 49.643002 | 246587000 |
2023-12-29 00:00:00+00:00 | 49.511375 | 49.521999 | 49.997002 | 48.750999 | 49.813000 | 389293000 |
2516 rows × 6 columns