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How do I get indices of N maximum values in a NumPy array?
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365
The simplest I've been able to come up with is:
In [1]: import numpy as np
In [2]: arr = np....
Selecting pandas column by location
... mind:
>>> df
A B C D
0 0.424634 1.716633 0.282734 2.086944
1 -1.325816 2.056277 2.583704 -0.776403
2 1.457809 -0.407279 -1.560583 -1.316246
3 -0.757134 -1.321025 1.325853 -2.513373
4 1.366180 -1.265185 -2.184617 0.881514
>>> df.iloc[:, ...
Cannot ping AWS EC2 instance
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answered May 30 '15 at 9:39
RakibRakib
8,9821010 gold badges5555 silver badges9090 bronze badges
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How to select rows from a DataFrame based on column values?
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4135
To select rows whose column value equals a scalar, some_value, use ==:
df.loc[df['column_name'...
pandas DataFrame: replace nan values with average of columns
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283
You can simply use DataFrame.fillna to fill the nan's directly:
In [27]: df
Out[27]:
...
Concatenate two slices in Go
I'm trying to combine the slice [1, 2] and the slice [3, 4] . How can I do this in Go?
7 Answers
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How does the Brainfuck Hello World actually work?
...ctual cell.
Take a look at ASCII table. For example, decimal code of ! is 33, while a is 97.
Well, lets imagine your BF program memory looks like:
...[0][0][*0*][0][0]...
Assuming standard input stands for a, if you use comma , operator, what BF does is read a decimal ASCII code 97 to memory:
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Regular expression to match DNS hostname or IP Address?
...lidIpAddressRegex = "^(([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])\.){3}([0-9]|[1-9][0-9]|1[0-9]{2}|2[0-4][0-9]|25[0-5])$";
ValidHostnameRegex = "^(([a-zA-Z0-9]|[a-zA-Z0-9][a-zA-Z0-9\-]*[a-zA-Z0-9])\.)*([A-Za-z0-9]|[A-Za-z0-9][A-Za-z0-9\-]*[A-Za-z0-9])$";
ValidIpAddressRegex matches valid IP...
Find MongoDB records where array field is not empty
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873
If you also have documents that don't have the key, you can use:
ME.find({ pictures: { $exists:...
Normalize data in pandas
... df
Out[92]:
a b c d
A -0.488816 0.863769 4.325608 -4.721202
B -11.937097 2.993993 -12.916784 -1.086236
C -5.569493 4.672679 -2.168464 -9.315900
D 8.892368 0.932785 4.535396 0.598124
In [93]: df_norm = (df - df.mean()) / (df.max() - df.min())
In [9...