Pandas: get string from specific column header

Question

Context:

i am new in Pandas and I need a function that creates new columns based on existing columns. The new columns name will have the name from the original column plus new characters (example: create a "As NEW" column from "As" column). Can i access the old column header string to make the name of the new column?

Problem:

i have df['columnA'] and need to get "columnA" string

Answer 1

If I understand you correctly, this may be what you're looking for.

You can use str.contains() for the columns, then use string formatting to create the new column name.

df = pd.DataFrame({'col1':['A', 'A', 'B','B'], 'As': ['B','B','C','C'], 'col2': ['C','C','A','A'], 'col3': [30,10,14,91]})
col = df.columns[df.columns.str.contains('As')]
df['%s New' % col[0]] = 'foo'
print (df)
   As   col1 col2  col3 As New
0  B    A    C    30    foo
1  B    A    C    10    foo
2  C    B    A    14    foo
3  C    B    A    91    foo

Answer 2

Assuming that you have an empty DataFrame df with columns, you could access the columns of df as a list with:

 >>> df.columns
Index(['columnA', 'columnB'], dtype='object')

.columns will allow you to overwrite the columns of df, but you don't need to pass in another Index. You can pass it a regular list, like so:

>>> df.columns = ['columna', 'columnb']
>>> df
Empty DataFrame
Columns: [columna, columnb]
Index: []

Answer 3

This can be done through the columns attribute.

cols = df.columns
# Do whatever operation you want on the list of strings in cols
df.columns = cols