The following is an extract of some test data:
| APNTPLID | APNTPLID | EPSLOCK | LOCK_S | UPL | UPLP | LOCK_MSIN | LOCK_MSOUT | OCSI | TCSI |
|---|---|---|---|---|---|---|---|---|---|
| 6&1&2 | 6&1&2 | EPSLOCK | 1 | 1 | 1 | 1 | 1 | YES | YES |
| 42&1&101&6&2 | 42&1&101&6&2 | EPSLOCK | 1 | 1 | 1 | 1 | 1 | YES | YES |
| 2&6&101 | 2&6&101 | EPSLOCK | 1 | 1 | 1 | 0 | 1 | YES | YES |
| 2&101&6 | 2&101&6 | 0 | 1 | 1 | 1 | 1 | 1 | YES | YES |
| 2&6&101 | 2&6&101 | EPSLOCK | 1 | 1 | 0 | 1 | 1 | YES | YES |
I have attempted, using Python, to extract the required columns ONLY if a record is Activated (NOT Deactivated). A record is deemed Deactivated ONLY when the following values occurs for the specific fields for each record, and is all present at the same time:
- EPSLOCK=EPSLOCK
- LOCK_S=1
- UPL=1
- UPLP=1
- LOCK_MSIN=1
- LOCK_MSOUT=1
Therefore, after running the script only the last 3 rows should be extracted - since the first 2 rows are Deactivated records.
I have tried the following Script but it extracts the Deactivated as well. Any assistance appreciated. (Really new to this)
import pandas as pd
file_path = "C:\\Users\\user1\\data\\testdata.csv"
data = pd.read_csv(file_path)
data = data[(data["EPSLOCK"] == "EPSLOCK") | (data["EPSLOCK"] == 0) | (data["LOCK_S"] == 1) | (data["LOCK_S"] == 0) | (data["UPL"] == 1) | (data["UPL"] == 0) | (data["UPLP"] == 1) | (data["UPLP"] == 0) | (data["LOCK_MSIN"] == 1) | (data["LOCK_MSIN"] == 0) | (data["LOCK_MSOUT"] == 1) | (data["LOCK_MSOUT"] == 0)]
data = data[["APNTPLID", "EPSLOCK", "APNTPLID", "LOCK_S", "UPL", "UPLP", "LOCK_MSIN", "LOCK_MSOUT", "OCSI", "TCSI"]]
data.to_csv("C:\\Users\\user1\\testresult.csv")
print(data)
CodePudding user response：
It seems to me that you are listing pretty much every possible combination. Also, you use | (or) instead of & (and) as all conditions need to be true simultaneously.
Based on your conditions of when something is deactivated, this would work:
data = df[~((df["EPSLOCK"] == "EPSLOCK")
& (df["LOCK_S"] == 1)
& (df["UPL"] == 1)
& (df["UPLP"] == 1)
& (df["LOCK_MSIN"] == 1)
& (df["LOCK_MSOUT"] == 1))]
in which ~ means that it should not be true.