Ojo | an open soure gtk media player for linux | Video Player library

You can do that with the following

df[df.columns[-1]][0]

By slicing with double square brackets you get a (2D) DataFrame.

It looks like you're trying to loop in 1D. You should use Series.iteritems:

Figured it out. After adding the penultimate element to the array, the program will use a for loop to iterate over the dictionary, and it will evaluate which key is not in the array, the one that is not there (as it will always be the last one) will be added automatically by the program. After this, the program breaks the while True loop of the original code

Use sort_index with axis=1:

Use Series.str.split and df.replace with pd.concat:

You can extract the column names from the Permutations column by splitting it with + sign. Similarly, you can extract data from FilePermutations column.

all(['None' in v for k, v in the_dictionary_list.items()])

This loops through the dictionary key value pairs and returns a True or False if 'None' is in the value. And then all checks if they are all true if one is false it will return False if all are True it returns true

The following solution was built by @christian from stackoverflow en español, the translation of his answer is the following:

Pandas DataFrames have a method called iterrorws() that returns a generator and we can iterate through it, this returns the row itself as a tuple that contains two objects, the first one is the index of the row and the second one is a Pandas Series that contains the values of the next columns.

I would not recommend joining the names with a +, you can simply leave them in list format since later we will need them as lists again and you can save that conversion to a list by avoiding using '+'.join(x).

IIUC, one way using pandas.Series.str.cat: