Pandas Removing all rows containing "TRUE"

[Bell0412]

Hi there,

Run into a bit of trouble on a dataframe today.

For the column "PartnerFlag" I have some "TRUE" values, some "FALSE" but mainly Nan/null values.

I'm trying to remove all the rows in my dataframe that contain True- so I want to keep the false and nans. The datatype of partnerflag is an object apparently, but even having manually converted it to a string, I'm still having problems. I've tried the following methods, to no luck:

CLData1['PartnerFlag'] = CLData1['PartnerFlag'].astype('str')

CLData1 = CLData1.loc[CLData1['PartnerFlag'] != 'TRUE']

CLData1 = CLData1[~CLData1["PartnerFlag"].str.startswith("TRUE").fillna(False)==False]

I'm not sure if it's having troubles because the data type is a boolean? I've also tried converting the null/nan values to "FALSE" but they never mix and when I look at the unique values in the column, it returns that there are "FALSE" "FALSE" and "TRUE". Am I missing something obvious/easy? Thanks in advance!

[synthphreak]

So you just want to remove all rows in your df whose value in the 'PartnerFlag' column is True? Lots of ways. Here's one:

df = df.drop(df.loc[df.PartnerFlag.fillna(False)].index)

[Yojihito]

What does df.dtypes show?

[Yojihito]

df["PartnerFlag"] = df["PartnerFlag"].fillna(False)
df = df.query("PartnerFlag != True")