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Costa.Gustavo
Costa.Gustavo

Reputation: 849

Splitting columns in pandas

I have pandas dataframe with the following structure:

df1 = pd.DataFrame({'id': 1, 'coords':{0: [(-43.21,-22.15),(-43.22,-22.22)]}})

How can I separate the values from the coords column so that the first item in each list forms the column called latitude and the second the column called longitude, as below?

id|  latitude     |longitude
1 |(-43.21,-43.22)|(-22.15, -22.22)

Upvotes: 0

Views: 65

Answers (4)

Rean
Rean

Reputation: 56

take the tuple for lat:

lat = [(x[0][0],x[1][0]) for x in df1['coords'].values]
df1['latitude'] = lat

same as for longt:

longt = [(x[0][1],x[1][1]) for x in df1['coords'].values]
df1['longtitude'] = longt

drop coords columns:

df1.drop(columns='coords')

hope this helps!

Upvotes: 0

J. Doe
J. Doe

Reputation: 3634

Simply using the .str accessor

df1['latitude'] = df1['coords'].str[0]
df1['longitude'] = df1['coords'].str[1]

Time difference:

df1['latitude'] = df1['coords'].str[0] 
# 539 µs ± 15.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
df1['latitude'] = df1.coords.apply(lambda x: x[0]) 
# 624 µs ± 16.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

Upvotes: 0

BENY
BENY

Reputation: 323266

Using join with column explode 

df1=df1.join(pd.DataFrame(df1.coords.tolist(),index=df1.index,columns=['latitude','longitude']))

Out[138]: 
   id                                coords          latitude         longitude
0   1  [(-43.21, -22.15), (-43.22, -22.22)]  (-43.21, -22.15)  (-43.22, -22.22)

Upvotes: 1

Juan C
Juan C

Reputation: 6132

apply is a straightforward way:

df1['latitude'] = df1.coords.apply(lambda x: x[0])
df1['longitude'] = df1.coords.apply(lambda x: x[1])

Output:

   id                                coords          latitude         longitude
0   1  [(-43.21, -22.15), (-43.22, -22.22)]  (-43.21, -22.15)  (-43.22, -22.22)

Upvotes: 0

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