Good day,
I have a column from a data frame here:
A 23 10 11 22 My objective is to create a new column and associate the numbers like this:
A file_number 23 8 10 6 11 6 22 8 As seen above both numbers 22, 23 are associated with the number 8 and numbers 10 and 11 are associated with number 6. How can I create such a column? Thanks in advance
I think need if need create new values by first value of number with map by dictionary:
print (df['A'].apply(type)) 0 <class 'int'> 1 <class 'int'> 2 <class 'int'> 3 <class 'int'> Name: A, dtype: object df['new'] = (df['A'] // 10).map({1:6, 2:8}) print (df) A new 0 23 8 1 10 6 2 11 6 3 22 8 Detail:
print ((df['A'] // 10)) 0 2 1 1 2 1 3 2 Name: A, dtype: int64 Another solution works with strings:
df['new'] = df['A'].astype(str).str[0].map({'1':6, '2':8}) print (df['A'].apply(type)) 0 <class 'str'> 1 <class 'str'> 2 <class 'str'> 3 <class 'str'> Name: A, dtype: object df['new'] = df['A'].str[0].map({'1':6, '2':8}) If need convert positive number to first numeric is possible use this solution converted to numpy/pandas:
df['new'] = df['A'] // 10 ** np.log10(df['A'].values).astype(int) print (df) A new 0 2 2 1 10000 1 2 110 1 3 220000 2 
dictionary.map. What if im working with a bigger data frame with grouping alot of numbers to one number and there are several of these cases. Is there a way to index or slice or another way...? @jezraelmap by dictioanry is what need. Do you understand it correct, df['A'] // 10 is not possible use because different length of numbers like 456, 41, 7 ?
Aandfile_number?