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Concatenating two one-dimensional NumPy arrays
... as separate arguments.
From the NumPy documentation:
numpy.concatenate((a1, a2, ...), axis=0)
Join a sequence of arrays together.
It was trying to interpret your b as the axis parameter, which is why it complained it couldn't convert it into a scalar.
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How does numpy.histogram() work?
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169
A bin is range that represents the width of a single bar of the histogram along the X-axis. Yo...
Shuffle two list at once with same order
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211
You can do it as:
import random
a = ['a', 'b', 'c']
b = [1, 2, 3]
c = list(zip(a, b))
rando...
Output data from all columns in a dataframe in pandas [duplicate]
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answered Jul 6 '12 at 12:18
eumiroeumiro
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Summarizing multiple columns with dplyr? [duplicate]
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#> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 3.08 2.98 2.98 2.91
#> 2 2 3.03 3.04 2.97 2.87
#> 3 3 2.85 2.95 2.95 3.06
If you want to summarize only certain columns, use summarise_at or summarise_if functions.
Alternatively, the purrrl...
get list from pandas dataframe column
... cast 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['o...
If vs. Switch Speed
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185
The compiler can build jump tables where applicable. For example, when you use the reflector t...
How can I obtain the element-wise logical NOT of a pandas Series?
...: s = pd.Series([True, True, False, True])
In [8]: ~s
Out[8]:
0 False
1 False
2 True
3 False
dtype: bool
Using Python2.7, NumPy 1.8.0, Pandas 0.13.1:
In [119]: s = pd.Series([True, True, False, True]*10000)
In [10]: %timeit np.invert(s)
10000 loops, best of 3: 91.8 µs per loop
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