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This is probably easy, but I have the following data:
In data frame 1:
index dat1 0 9 1 5
In data frame 2:
index dat2 0 7 1 6
I want a data frame with the following form:
index dat1 dat2 0 9 7 1 5 6
I"ve tried using the
append method, but I get a cross join (i.e. cartesian product).
What"s the right way to do this?
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Why is it string.join(list) instead of list.join(string)?
This has always confused me. It seems like this would be nicer:
my_list = ["Hello", "world"] print(my_list.join("-")) # Produce: "Hello-world"
my_list = ["Hello", "world"] print("-".join(my_list)) # Produce: "Hello-world"
Is there a specific reason it is like this?
It"s because any iterable can be joined (e.g, list, tuple, dict, set), but its contents and the "joiner" must be strings.
"_".join(["welcome", "to", "stack", "overflow"]) "_".join(("welcome", "to", "stack", "overflow"))
Using something other than strings will raise the following error:
TypeError: sequence item 0: expected str instance, int found
This was discussed in the String methods... finally thread in the Python-Dev achive, and was accepted by Guido. This thread began in Jun 1999, and
str.join was included in Python 1.6 which was released in Sep 2000 (and supported Unicode). Python 2.0 (supported
str methods including
join) was released in Oct 2000.
- There were four options proposed in this thread:
joinas a built-in function
- Guido wanted to support not only
tuples, but all sequences/iterables.
seq.reduce(str)is difficult for newcomers.
seq.join(str)introduces unexpected dependency from sequences to str/unicode.
join()as a built-in function would support only specific data types. So using a built-in namespace is not good. If
join()supports many datatypes, creating an optimized implementation would be difficult, if implemented using the
__add__method then it would ve
- The separator string (
sep) should not be omitted. Explicit is better than implicit.
Here are some additional thoughts (my own, and my friend"s):
- Unicode support was coming, but it was not final. At that time UTF-8 was the most likely about to replace UCS2/4. To calculate total buffer length of UTF-8 strings it needs to know character coding rule.
- At that time, Python had already decided on a common sequence interface rule where a user could create a sequence-like (iterable) class. But Python didn"t support extending built-in types until 2.2. At that time it was difficult to provide basic
iterableclass (which is mentioned in another comment).
Guido"s decision is recorded in a historical mail, deciding on
Funny, but it does seem right! Barry, go for it...
Guido van Rossum
join() method is in the string class, instead of the list class?
I agree it looks funny.
Historical note. When I first learned Python, I expected join to be a method of a list, which would take the delimiter as an argument. Lots of people feel the same way, and there‚Äôs a story behind the join method. Prior to Python 1.6, strings didn‚Äôt have all these useful methods. There was a separate string module which contained all the string functions; each function took a string as its first argument. The functions were deemed important enough to put onto the strings themselves, which made sense for functions like lower, upper, and split. But many hard-core Python programmers objected to the new join method, arguing that it should be a method of the list instead, or that it shouldn‚Äôt move at all but simply stay a part of the old string module (which still has lots of useful stuff in it). I use the new join method exclusively, but you will see code written either way, and if it really bothers you, you can use the old string.join function instead.
--- Mark Pilgrim, Dive into Python
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Abu Dhabi | 2023-04-01
join is always a bit confusing 😭 Append column to pandas dataframe is not the only problem I encountered. Will get back tomorrow with feedback
Munchen | 2023-04-01
Python functions is always a bit confusing 😭 Append column to pandas dataframe is not the only problem I encountered. I just hope that will not emerge anymore
London | 2023-04-01
code Python module is always a bit confusing 😭 Append column to pandas dataframe is not the only problem I encountered. I am just not quite sure it is the best method