key is just a variable name.
for key in d:
will simply loop over the keys in the dictionary, rather than the keys and values. To loop over both key and value you can use the following:
For Python 3.x:
for key, value in d.items():
For Python 2.x:
for key, value in d.iteritems():
To test for yourself, change the word key to poop.
In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better.
This is also available in 2.7 as viewitems().
The operation items() will work for both 2 and 3, but in 2 it will return a list of the dictionary's (key, value) pairs, which will not reflect changes to the dict that happen after the items() call. If you want the 2.x behavior in 3.x, you can call list(d.items()).
key is just a variable name.
for key in d:
will simply loop over the keys in the dictionary, rather than the keys and values. To loop over both key and value you can use the following:
For Python 3.x:
for key, value in d.items():
For Python 2.x:
for key, value in d.iteritems():
To test for yourself, change the word key to poop.
In Python 3.x, iteritems() was replaced with simply items(), which returns a set-like view backed by the dict, like iteritems() but even better.
This is also available in 2.7 as viewitems().
The operation items() will work for both 2 and 3, but in 2 it will return a list of the dictionary's (key, value) pairs, which will not reflect changes to the dict that happen after the items() call. If you want the 2.x behavior in 3.x, you can call list(d.items()).
It's not that key is a special word, but that dictionaries implement the iterator protocol. You could do this in your class, e.g. see this question for how to build class iterators.
In the case of dictionaries, it's implemented at the C level. The details are available in PEP 234. In particular, the section titled "Dictionary Iterators":
Dictionaries implement a tp_iter slot that returns an efficient iterator that iterates over the keys of the dictionary. [...] This means that we can write
for k in dict: ...which is equivalent to, but much faster than
for k in dict.keys(): ...as long as the restriction on modifications to the dictionary (either by the loop or by another thread) are not violated.
Add methods to dictionaries that return different kinds of iterators explicitly:
for key in dict.iterkeys(): ... for value in dict.itervalues(): ... for key, value in dict.iteritems(): ...This means that
for x in dictis shorthand forfor x in dict.iterkeys().
In Python 3, dict.iterkeys(), dict.itervalues() and dict.iteritems() are no longer supported. Use dict.keys(), dict.values() and dict.items() instead.
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Hello, I'm trying to compare the kappa scores for one person against other people. I want to generate a dataframe that has the kappa for person A vs person B, person A vs person C, person A vs person D, etc.
To do this, I was thinking of reading in a everyone's scores that they gave as a dataframe, and assigning them to a dictionary. So something like {person B : person_B_scores_df, person C: person_C_scores}
But I can't figure out how to iterate over a for loop and add the key pairings to a dictionary. I keep getting a key error. Here is my code.
## Create list of raters
rater_list = ["person_A", "person_B", "person_C", "person_D"]
rater_dict = {}
## Pull in each rater's scores and add them key/value pairing in rater_dict
for name in rater_list:
rater_df = pd.read_csv(input_path/f"rater_scores_{name}.csv")
rater_dict[name].append(rater_df)
## Also tried the following!! - The code below only appends the last person in the rater list to the dictionary
#for name in rater_list:
# rater_df = pd.read_csv(input_path/f"rater_scores_{name}.csv")
# rater_dict={name:rater_df}