I have a list of ids (docids), and I have a dataframe with ids and associated columns (entity, gender). I need to check if x id from the list of ids is in the dataframe id column. If x is in the dataframe, I then want the string from the 'gender' column. I am checking first to avoid a key error when I iterate through my list of ids, as some of the IDs are not in the dataframe. My list of ids is (abbreviated) docids = [1,2] Dataframe gdf: docid entity Gender Gender Probability Gender Count 0 0 david l. aagesen male 1.00 3489607 1 1 robert t. aangeenbrug male 1.00 1566661 The following code returns false, even though I have confirmed docids[1] (the value of which is 1) is in the docid column: docids[1] in gdf['docid'].values Whereas this code returns true which is accurate. 1 in gdf['docid'].values When I run this code, I get an empty series, but when I run it with 1 instead of docids[1] I get the actual row of data: gdf[(gdf['docid'] == docids[1])] This is how I am trying to use in the future. Right now, when I run the code, it returns false on every ID and results in 3 empty lists. mids = [] # male IDs fids = [] # female ids uids = [] # unknown for d in docids: intd = int(d) if d in gdf['docid'].values == True: row = gdf[(gdf['docid'] == intd)] gender = row.iloc[0]['Gender'] if gender == 'male': mids.append(intd) elif gender == 'female': fids.append(intd) else: uids.append(intd) Continue reading...
