CordovaCann (LVRLF) Operating Expenses (2009 - 2022)
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Analysis
CordovaCann (LVRLF) Operating Expenses (2009 - 2022) Analysis & Trends
Peer Set
Peer Comparison
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2022 | 1.43 Mn |
| Jun 30, 2021 | 2.07 Mn |
| Mar 31, 2021 | 1.19 Mn |
| Jun 30, 2020 | 1.46 Mn |
| Mar 31, 2020 | 10,694.64 |
| Dec 31, 2019 | 807,394.02 |
| Sep 30, 2019 | 682,111.80 |
| Jun 30, 2019 | 1.37 Mn |
| Mar 31, 2019 | 957,460.13 |
| Dec 31, 2018 | 1.12 Mn |
| Sep 30, 2018 | 735,044.26 |
| Jun 30, 2018 | 725,577.51 |
| Mar 31, 2018 | 2.79 Mn |
| Dec 31, 2017 | 310,100.20 |
| Sep 30, 2017 | 19,776.48 |
| Jun 30, 2017 | 20,191.90 |
| Mar 31, 2017 | 15,834.13 |
| Dec 31, 2016 | 14,537.33 |
| Sep 30, 2016 | 16,034.23 |
| Jun 30, 2016 | -1,157.59 |
API Access
CordovaCann Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=LVRLF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LVRLF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=LVRLF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();