CODEWITHSUNDEEP
pythonpandasperformance
BestSithInEU
BestSithInEU

Reputation: 81

Splitting Data Python

Hello everyone i have data like this;

0 1 2
-- state: US state (by number) - not counted a... but if considered should be consided nominal (nominal)
-- county: numeric code for county - not predi... and many missing values (numeric) NaN
... ... ...

But i would like to transform into this;

0 1 2
state US state (by number) - not counted a ... but if considered should be consided nominal (nominal)
county numeric code for county - not predi ... and many missing values (numeric) NaN
... ..... ....

or simply;

0
state
country
....

and i wrote this code, but i wonder that is there any possible way to do that quicker..

variable_names = pd.read_csv("path", header = None)

df = variable_names[0]
df = df.str.split(': ', expand = True)

df = df[0]
df = df.str.split('-- ', expand = True)

Upvotes: 0

Views: 63

Answers (1)

Sammy J
Sammy J

Reputation: 1066

One way to solve this is:

# This becomes a pandas dataframe.
variable_names = pd.read_csv("path", header = None)

# Using simple apply works on all rows.
variable_names[0] = variable_names[0].apply(lambda x:x.split(': ')[0])
variable_names[0] = variable_names[0].apply(lambda x:x.split('-- ')[1])

Please check if this works for you.

Upvotes: 1

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