Filter data into new dataframe as main dataframe is being populated

[cubangt]

Here is my test script updated and working as expected. Just need to replace the "statusResults" dataframe with the dynamically generated one in the main script, but i feel good about this working in production.

# THIS IS TEMPORARY UNTIL MOVED TO REAL SCRIPT(THIS WILL BE THE PING RESULTS BEFORE WRITING TO CSV)
statusResults = pd.read_csv("Register_ip_output_20231021_233512.csv",names=['IP', 'Store', 'Register','Status', 'Datetime'])

# Compute what % of registers are offline
by_store = statusResults.groupby("Store")
status = by_store["Status"]
report = pd.concat([status.size(), status.sum()], axis=1).reset_index()
report.columns = ["Store", "Register Count", "Percentage"]
report["Percentage"] = report["Percentage"] / report["Register Count"] * 100
statuscntUp = len(statusResults[statusResults["Status"] == False])

# USED TO CALCULATE NUMBER OF STORES WITH A % OF REGISTERS DOWN
percentDown = len(report[report["Percentage"] != 0].index)
# RETURNS THE TOTAL NUMBER OF REGISTERS CHECKED
RegisterCount = report["Register Count"].sum()
# TOTAL CHAIN % OF REGISTERS UP
TotalPercentUp = str(int(statuscntUp / RegisterCount * 100)) + "%"

# LIST OF STORES FOR DISPLAYING ON SCREEN(FORMATTED)
TwentyStores = ','.join(str(v) for v in report[(report["Percentage"] > 20) & (report["Percentage"] < 50)]["Store"].values)
# GETS COUNT OF STORES WITH MORE THAN 20%
TwentyPercent = len(report[(report["Percentage"] > 20) & (report["Percentage"] < 50)]["Store"].values)

# GETS COUNT OF STORES WITH MORE THAN 50%
FiftyPercent = len(report[report["Percentage"] >= 50]["Store"].values)
# LIST OF STORES FOR DISPLAYING ON SCREEN(FORMATTED)
FiftyStores = ','.join(str(v) for v in report[report["Percentage"] >= 50]["Store"].values)