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What is the PostgreSQL equivalent for ISNULL()
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edited Jan 14 '12 at 2:28
Erwin Brandstetter
439k9696 gold badges809809 silver badges969969 bronze badges
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How to overcome TypeError: unhashable type: 'list'
...pend(value)
else:
d[key] = [value]
print d
# {'AAA': ['111', '112'], 'AAC': ['123'], 'AAB': ['111']}
Note that if you are using Python 3.x, you'll have to make a minor adjustment to get it work properly. If you open the file with rb, you'll need to use line = line.split(b'x') (which mak...
How to manually deprecate members
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273
You can use the Available tag, for example :
@available(*, deprecated)
func myFunc() {
/...
How to subtract 2 hours from user's local time?
...e JavaScript code block that will allow me to display the local time minus 2 hours?
2 Answers
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How to generate random SHA1 hash to use as ID in node.js?
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edited May 23 '17 at 12:10
Community♦
111 silver badge
answered Feb 23 '12 at 6:28
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What is the difference between Int and Integer?
...ers may
recognise the "bignum" type here.
"Int" is the more common 32 or 64 bit
integer. Implementations vary,
although it is guaranteed to be at
least 30 bits.
Source: The Haskell Wikibook. Also, you may find the Numbers section of A Gentle Introduction to Haskell useful.
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Can dplyr package be used for conditional mutating?
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220
Use ifelse
df %>%
mutate(g = ifelse(a == 2 | a == 5 | a == 7 | (a == 1 & b == 4), 2,
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Converting NumPy array into Python List structure?
How do I convert a NumPy array to a Python List (for example [[1,2,3],[4,5,6]] ), and do it reasonably fast?
5 Answers
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What is the most efficient way to create a dictionary of two pandas Dataframe columns?
...: pd.Series(df.Letter.values,index=df.Position).to_dict()
Out[9]: {1: 'a', 2: 'b', 3: 'c', 4: 'd', 5: 'e'}
Speed comparion (using Wouter's method)
In [6]: df = pd.DataFrame(randint(0,10,10000).reshape(5000,2),columns=list('AB'))
In [7]: %timeit dict(zip(df.A,df.B))
1000 loops, best of 3: 1.27 ms...
Frequency table for a single variable
...s()?
>>> import pandas
>>> my_series = pandas.Series([1,2,2,3,3,3, "fred", 1.8, 1.8])
>>> my_series
0 1
1 2
2 2
3 3
4 3
5 3
6 fred
7 1.8
8 1.8
>>> counts = my_series.value_counts()
>>> counts
3 3
2 ...