Hi I have a following df:
sentence osm_id place 0 #SP486 in località Pianezzo, SENSO UNICO ALTER... 62053.0 ponte 1 In provincia di Modena frana sulla strada prov... 22165.0 samone 2 Provincia di Modena: Pavullo, frana lungo la s... 62053.0 ponte 3 Provincia di Modena: Pavullo, frana sulla sp 4... 22165.0 # 4 Provincia di Modena: Prignano, i lavori su una... NaN NaN
I would like to to add the latitude and longitude columns after the city name, while where there are NaN and # value I would like to leave new cells empty or with 0 value.
what I tried:
series = pd.Series(table['place']) if series.apply(lambda x: x==x): table['Lat'] = 0 table['Lon'] = 0 elif series.apply(lambda x: x!=x): table['Lat'] = table.place.apply(lambda x: coord_map[x][1]) table['Lon'] = table.place.apply(lambda x: coord_map[x][0])
the error that I get:
Traceback (most recent call last): File "c:/Users/user/GeoParsing/main.py", line 136, in <module> if series.apply(lambda x: x==x): File "C:UsersuserGeoParsingvenvlibsite-packagespandascoregeneric.py", line 1442, in __nonzero__ raise ValueError( ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
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Answer
You can try:
table['Lat'] = table.place.map(lambda x: 0 if (pd.isna(x) or (x == '#')) else coord_map[x][1]) table['Lon'] = table.place.map(lambda x: 0 if (pd.isna(x) or (x == '#')) else coord_map[x][0])