Extracting values to new columns with pandas

user_15682799 0
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I have a dataframe where the coordinates column comes in this format

[-7.821, 37.033]

I would like to create two columns where the first is lonand the second is lat

I've tried

my_dict = df_map['coordinates'].to_dict()
df_map_new = pd.DataFrame(list(my_dict.items()),columns = ['lon','lat'])

But the dictionary that is created does not split the values between , Instead it creates a dict with the following format

0: '[-7.821, 37.033]'

What is the best way to extract the values within [,] and put them into two new columns in the original dataframe df_map?

Thank you in advance!

pandas dataframe python
3 Answers

You can parse string:

pattern = r"\[(?P<lon>.*),\s*(?P<lat>.*)\]"
out = df_map['coordinates'].str.extract(pattern).astype(float)
print(out)

# Output
     lon     lat
0 -7.821  37.033
user_152399510

Convert values to lists by ast.literal_eval, then to lists instead dicts:

import ast

my_L = df_map['coordinates'].apply(ast.literal_eval).tolist()
df_map_new = pd.DataFrame(my_L,columns = ['lon','lat'])
user_29010020

Additionally to the answers already provided, you can also try this:

ser_lon = df['coordinates'].apply(lambda x: x[0])
ser_lat = df['coordinates'].apply(lambda x: x[1])

df_map['lon'] = ser_lon
df_map['lat'] = ser_lat
user_155906900
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