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Using numpy to build an array of all combinations of two arrays
... faster implementation:
@pv's solution
In [113]:
%timeit cartesian(([1, 2, 3], [4, 5], [6, 7]))
10000 loops, best of 3: 135 µs per loop
In [114]:
cartesian(([1, 2, 3], [4, 5], [6, 7]))
Out[114]:
array([[1, 4, 6],
[1, 4, 7],
[1, 5, 6],
[1, 5, 7],
[2, 4, 6],
[2...
Pandas index column title or name
...0]:
Column 1
foo
Apples 1
Oranges 2
Puppies 3
Ducks 4
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How to select rows from a DataFrame based on column values?
... three'.split(),
'C': np.arange(8), 'D': np.arange(8) * 2})
print(df)
# A B C D
# 0 foo one 0 0
# 1 bar one 1 2
# 2 foo two 2 4
# 3 bar three 3 6
# 4 foo two 4 8
# 5 bar two 5 10
# 6 foo one 6 12
# 7 foo three 7 14
pri...
What are the mathematical/computational principles behind this game?
...into the soup and you have the question:
Can we have a geometry with just 2 points? With 3 points? With 4? With 7?
There are still open questions regarding this problem but we do know this:
If there are geometries with Q points, then Q = n^2 + n + 1 and n is called the order of the geometry.
The...
Can dplyr package be used for conditional mutating?
...
220
Use ifelse
df %>%
mutate(g = ifelse(a == 2 | a == 5 | a == 7 | (a == 1 & b == 4), 2,
...
get list from pandas dataframe column
...st it with list(x).
import pandas as pd
data_dict = {'one': pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two': pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(data_dict)
print(f"DataFrame:\n{df}\n")
print(f"column types:\n{df.dtypes}")
col_one_list = df['one'...
Why does Math.round(0.49999999999999994) return 1?
....1 This is a specification bug, for precisely this one pathological case.2 Java 7 no longer mandates this broken implementation.3
The problem
0.5+0.49999999999999994 is exactly 1 in double precision:
static void print(double d) {
System.out.printf("%016x\n", Double.doubleToLongBits(d));
}
...
For each row return the column name of the largest value
...d() to make examples using sample reproducible):
DF <- data.frame(V1=c(2,8,1),V2=c(7,3,5),V3=c(9,6,4))
colnames(DF)[apply(DF,1,which.max)]
[1] "V3" "V1" "V2"
A faster solution than using apply might be max.col:
colnames(DF)[max.col(DF,ties.method="first")]
#[1] "V3" "V1" "V2"
...where ties...
Logical operators for boolean indexing in Pandas
...
219
When you say
(a['x']==1) and (a['y']==10)
You are implicitly asking Python to convert (a['x...
Is it possible to install another version of Python to Virtualenv?
I have a shared account in a web-hosting that has Python 2.4 installed, but my code is not compatible with 2.4. Is it possible to install Python 2.6 directly to Virtualenv?
...