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I have created a column with country name, and lattitude and longitude values in a single column. now i want the latitude value and longitude values in a different column.
code used to create the column.
df['Country_cord'] = df['Country'].apply(geolocator.geocode)
Thats how the output looks like.
0 (España, (40.0028028, -4.003104))
1 (United Kingdom, دبي, الإمارات العربيّة المتّ...
2 (France métropolitaine, France, (46.603354, 1....
3 (United States of America, (39.7837304, -100.4...
4 (Italia, (42.6384261, 12.674297))
5 (Deutschland, Europe, (51.0834196, 10.4234469))
6 (Argentina, (-34.9964963, -64.9672817))
7 (Ireland, (52.865196, -7.9794599))
8 (België / Belgique / Belgien, (50.6407351, 4.6...
9 (מדינת ישראל, (30.8760272, 35.0015196))
10 (Schweiz/Suisse/Svizzera/Svizra, (46.7985624, ...
11 (Nederland, (52.2379891, 5.53460738161551))
12 (Brasil, (-10.3333333, -53.2))
13 (Portugal, (40.033265, -7.8896263))
14 (Australia, (-24.7761086, 134.755))
15 (Danmark, (55.670249, 10.3333283))
16 (Maroc ⵍⵎⵖⵔⵉⴱ المغرب, (31.1728192, -7.3366043))
17 (Ciudad de México, Cuauhtémoc, CDMX, 06060, Mé...
18 (Canada, (61.0666922, -107.9917071))
19 (Sverige, (59.6749712, 14.5208584))
i want output to be in a form where i have a column for latitude and one column for longitude.
df[lat] df[lon]
40.0028028 46.603354
46.603354 1.8883335
333
Split column by delimiter into multiple columns Apply the pandas series str. split() function on the “Address” column and pass the delimiter (comma in this case) on which you want to split the column. Also, make sure to pass True to the expand parameter.
split() function is used to break up single column values into multiple columns based on a specified separator or delimiter. The Series. str. split() function is similar to the Python string split() method, but split() method works on the all Dataframe columns, whereas the Series.
Tuple assignment In Python, you can call the split() method on a string and pass in an argument to split the string on. We can split the string below, my email address, in half on the @ symbol since there is just one in the string. This operation returns a list.
split() Pandas provide a method to split string around a passed separator/delimiter. After that, the string can be stored as a list in a series or it can also be used to create multiple column data frames from a single separated string.
Zipping generator expressions on numpy arrays are efficient for this:
import pandas as pd
df = pd.DataFrame([[('Country1', (341.123, 4534.123))],
[('Country2', (341.123, 4534.123))],
[('Country3', (341.123, 4534.123))],
[('Country4', (341.123, 4534.123))]],
columns=['Series1'])
df['Lat'], df['Lon'] = list(zip(*((x[1][0], x[1][1]) for x in df['Series1'].values)))
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