keyerror

I have a dict inside a dict: { '123456789': {u'PhoneOwner': u'Bob', 'Frequency': 0}, '98765431': {u'PhoneOwner': u'Sarah', 'Frequency': 0}, } The idea is to scan a list of calls made by numbers and compare against the dict, increasing the frequency each time a match is found. When I run the script: try: phoneNumberDictionary[int(line)]['Frequency'] += 1 except KeyError: phoneNumberDictionary[int(line)]['Frequency'] = 1 I get error: KeyError: '18667209918' (Where 18667209918 is the number that is currently being searched) Yet when I print the dict and just search for that number I can find it

I am using pandas 0.12.0 in ipython3 on Ubuntu 13.10, in order to wrangle large tab-delimited datasets in txt files. Using read_table to create a DataFrame from the txt appears to work, and the first row is read as a header, but attempting to access the first column using its name as an index throws a KeyError. I don't understand why this happens, given that the column names all appear to have been read correctly, and every other column can be indexed in this way. The data looks like this: RECORDING_SESSION_LABEL LEFT_GAZE_X LEFT_GAZE_Y RIGHT_GAZE_X RIGHT_GAZE_Y VIDEO_FRAME_INDEX VIDEO_NAME 73

Trying to combine two data frames when a datetime object from one dataframe is within a datetime object range in the other. Keep getting: KeyError: 'cannot use a single bool to index into setitem' on this line of code in the second chunk I posted. gametaxidf.loc[arrivemask, 'relevant'] = 1 I'm assuming it would happen on the following line with a similar command as well. This is the part giving me trouble: with open('/Users/benjaminprice/Desktop/TaxiCombined/Data/combinedtaxifiltered.csv', 'w') as csvfile: fieldnames1 = ['index','pickup_datetime', 'dropoff_datetime', 'pickup_long', 'pickup_lat