I have one field in a pandas DataFrame that was imported as string format. It should be a datetime variable. How do I convert it to a datetime column and then filter based on date.
Example:
- DataFrame Name: raw_data
- Column Name: Mycol
- Value Format in Column: "05SEP2014:00:00:00.000"
Convert Pandas Column to DateTime filter: Questions
List comprehension vs. lambda + filter
5 answers
I happened to find myself having a basic filtering need: I have a list and I have to filter it by an attribute of the items.
My code looked like this:
my_list = [x for x in my_list if x.attribute == value]
But then I thought, wouldn"t it be better to write it like this?
my_list = filter(lambda x: x.attribute == value, my_list)
It"s more readable, and if needed for performance the lambda could be taken out to gain something.
Question is: are there any caveats in using the second way? Any performance difference? Am I missing the Pythonic Way‚Ñ¢ entirely and should do it in yet another way (such as using itemgetter instead of the lambda)?
Answer #1
It is strange how much beauty varies for different people. I find the list comprehension much clearer than filter
+lambda
, but use whichever you find easier.
There are two things that may slow down your use of filter
.
The first is the function call overhead: as soon as you use a Python function (whether created by def
or lambda
) it is likely that filter will be slower than the list comprehension. It almost certainly is not enough to matter, and you shouldn"t think much about performance until you"ve timed your code and found it to be a bottleneck, but the difference will be there.
The other overhead that might apply is that the lambda is being forced to access a scoped variable (value
). That is slower than accessing a local variable and in Python 2.x the list comprehension only accesses local variables. If you are using Python 3.x the list comprehension runs in a separate function so it will also be accessing value
through a closure and this difference won"t apply.
The other option to consider is to use a generator instead of a list comprehension:
def filterbyvalue(seq, value):
for el in seq:
if el.attribute==value: yield el
Then in your main code (which is where readability really matters) you"ve replaced both list comprehension and filter with a hopefully meaningful function name.
Answer #2
This is a somewhat religious issue in Python. Even though Guido considered removing map
, filter
and reduce
from Python 3, there was enough of a backlash that in the end only reduce
was moved from built-ins to functools.reduce.
Personally I find list comprehensions easier to read. It is more explicit what is happening from the expression [i for i in list if i.attribute == value]
as all the behaviour is on the surface not inside the filter function.
I would not worry too much about the performance difference between the two approaches as it is marginal. I would really only optimise this if it proved to be the bottleneck in your application which is unlikely.
Also since the BDFL wanted filter
gone from the language then surely that automatically makes list comprehensions more Pythonic ;-)
How do I do a not equal in Django queryset filtering?
5 answers
In Django model QuerySets, I see that there is a __gt
and __lt
for comparative values, but is there a __ne
or !=
(not equals)? I want to filter out using a not equals. For example, for
Model:
bool a;
int x;
I want to do
results = Model.objects.exclude(a=True, x!=5)
The !=
is not correct syntax. I also tried __ne
.
I ended up using:
results = Model.objects.exclude(a=True, x__lt=5).exclude(a=True, x__gt=5)
Answer #1
You can use Q objects for this. They can be negated with the ~
operator and combined much like normal Python expressions:
from myapp.models import Entry
from django.db.models import Q
Entry.objects.filter(~Q(id=3))
will return all entries except the one(s) with 3
as their ID:
[<Entry: Entry object>, <Entry: Entry object>, <Entry: Entry object>, ...]
Convert Pandas Column to DateTime sep: Questions
How to print number with commas as thousands separators?
5 answers
I am trying to print an integer in Python 2.6.1 with commas as thousands separators. For example, I want to show the number 1234567
as 1,234,567
. How would I go about doing this? I have seen many examples on Google, but I am looking for the simplest practical way.
It does not need to be locale-specific to decide between periods and commas. I would prefer something as simple as reasonably possible.
Answer #1
Locale unaware
"{:,}".format(value) # For Python ≥2.7
f"{value:,}" # For Python ≥3.6
Locale aware
import locale
locale.setlocale(locale.LC_ALL, "") # Use "" for auto, or force e.g. to "en_US.UTF-8"
"{:n}".format(value) # For Python ≥2.7
f"{value:n}" # For Python ≥3.6
Reference
Per Format Specification Mini-Language,
The
","
option signals the use of a comma for a thousands separator. For a locale aware separator, use the"n"
integer presentation type instead.
Answer #2
I got this to work:
>>> import locale
>>> locale.setlocale(locale.LC_ALL, "en_US")
"en_US"
>>> locale.format("%d", 1255000, grouping=True)
"1,255,000"
Sure, you don"t need internationalization support, but it"s clear, concise, and uses a built-in library.
P.S. That "%d" is the usual %-style formatter. You can have only one formatter, but it can be whatever you need in terms of field width and precision settings.
P.P.S. If you can"t get locale
to work, I"d suggest a modified version of Mark"s answer:
def intWithCommas(x):
if type(x) not in [type(0), type(0L)]:
raise TypeError("Parameter must be an integer.")
if x < 0:
return "-" + intWithCommas(-x)
result = ""
while x >= 1000:
x, r = divmod(x, 1000)
result = ",%03d%s" % (r, result)
return "%d%s" % (x, result)
Recursion is useful for the negative case, but one recursion per comma seems a bit excessive to me.
How would you make a comma-separated string from a list of strings?
5 answers
What would be your preferred way to concatenate strings from a sequence such that between every two consecutive pairs a comma is added. That is, how do you map, for instance, ["a", "b", "c"]
to "a,b,c"
? (The cases ["s"]
and []
should be mapped to "s"
and ""
, respectively.)
I usually end up using something like "".join(map(lambda x: x+",",l))[:-1]
, but also feeling somewhat unsatisfied.
Answer #1
my_list = ["a", "b", "c", "d"]
my_string = ",".join(my_list)
"a,b,c,d"
This won"t work if the list contains integers
And if the list contains non-string types (such as integers, floats, bools, None) then do:
my_string = ",".join(map(str, my_list))