Create new variable from DataFrame with names and set them as False boolean values-CodePudding

I have an pandas DataFrame that looks like this:

output:
        0                    1               3         ...
0     Subject            Importance         Hour       ...
1   Linear Algebra       Mandatory        Afternoon    ...
2   Data Science         Optional          Morning     ...
3   Data Structure       Mandatory          Night      ...
4      ...                   ...             ...

What I know so far is that, I can get the value of the Subject with:

df[0].tolist()

That will generate an list like:

['Linear Algebra', 'Data Science', 'Data Structure', ...]

But I need to create an dictionary that has the name of the subject, and the value defined as False

subject_dict = { 
    'Linear Algebra': False, 
    'Data Science' : False,
    'Data Structure': False
}

So that I can access them in order to modify from false to true. My first though was to use a dictionary, but thinking right know I may use also with a list.

How can I solve this?

I've tried:

subject_dict = df[0].to_dict()

but it didn't work.

Perhaps in a list but how it's going to be the iteration?

CodePudding user response：

You can use dict-comprehension:

dct = {s: False for s in df[0][1:]]

Or use dict.fromkeys:

dct = dict.fromkeys(df[0][1:], False)

Output:

>>> dct
{'Linear Algebra': False,
 'Data Science': False,
 'Data Structure': False}