CODEWITHSUNDEEP
pythonpandas
Lumos
Lumos

Reputation: 610

Too many values to unpack (expected 2) [list]

I have a dataset that contain 4 columns: "Date", "Num_week", "Calendar"

df.head() looks like:

    Date    Num_week    Calendar
412 2012-01-01  1      (2012, 1)
413 2012-01-02  2      (2012, 1)
414 2012-01-03  2      (2012, 1)
415 2012-01-04  2      (2012, 1)
416 2012-01-05  2      (2012, 1)

I sord values in column: sorted(list(set(date_week['calendar'])))

result:

['(2012, 1)',
 '(2012, 10)',
 '(2012, 11)',
 '(2012, 12)',
 '(2012, 2)',
 '(2012, 3)', etc.

And I try to get year and month separeted in loop.

for year, month in list(set(date_week['calendar'])):
    print(year, month)

But get ValueError:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-168-cf01e0d2888e> in <module>()
----> 1 for year, month in list(set(date_week['calendar'])):
      2     print(year, month)

ValueError: too many values to unpack (expected 2)

I've already tried use .items() and get wrong result.

Could you help me to deal with this problem?

Upvotes: 1

Views: 2671

Answers (2)

Suhas_Pote
Suhas_Pote

Reputation: 4590

date_week

           Date  Num_week   Calender
412  2012-01-01         1  (2012, 1)
413  2012-01-02         2  (2012, 1)
414  2012-01-03         2  (2012, 1)
415  2012-01-04         2  (2012, 1)
416  2012-01-05         2  (2012, 1)

Solution 1: Get output in list

l = list(zip(*df['Calender']))
[(2012, 2012, 2012, 2012, 2012), (1, 1, 1, 1, 1)]

OR

y,m = list(zip(*df['Calender']))
year = list(y)
month = list(m)

Output:

print(year)
[2012, 2012, 2012, 2012, 2012]

print(month)
[1, 1, 1, 1, 1]

Solution 2: You can create separate dataframe columns

ym = pd.DataFrame(df['Calender'].values.tolist(), columns=['year','month'], index=date_week.index)
ym

     year  month
412  2012      1
413  2012      1
414  2012      1
415  2012      1
416  2012      1

and merge with existing dataframe

date_week_new = pd.concat([df, ym],axis=1)
date_week_new 

           Date  Num_week   Calender  year  month
412  2012-01-01         1  (2012, 1)  2012      1
413  2012-01-02         2  (2012, 1)  2012      1
414  2012-01-03         2  (2012, 1)  2012      1
415  2012-01-04         2  (2012, 1)  2012      1
416  2012-01-05         2  (2012, 1)  2012      1

Upvotes: 1

jezrael
jezrael

Reputation: 863291

Problem is there are no tuples, but string repr of tuples, so need converting first:

import ast
date_week['Calendar'] = date_week['Calendar'].apply(ast.literal_eval)

So possible use your solution or alternative:

for year, month in date_week['Calendar'].unique():
    print(year, month)
    2012 1

EDIT: Alternative solution with Series.str.findall and converting to tuples:

date_week['Calendar'] = date_week['Calendar'].str.findall('\d+').apply(tuple)
print (date_week)
           Date  Num_week   Calendar
412  2012-01-01         1  (2012, 1)
413  2012-01-02         2  (2012, 1)
414  2012-01-03         2  (2012, 1)
415  2012-01-04         2  (2012, 1)
416  2012-01-05         2  (2012, 1)

Upvotes: 1

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