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When should I use Lazy?
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James Michael HareJames Michael Hare
34.8k99 gold badges6666 silver badges8080 bronze badges
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How to replace NaN values by Zeroes in a column of a Pandas Dataframe?
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In [7]: df
Out[7]:
0 1
0 NaN NaN
1 -0.494375 0.570994
2 NaN NaN
3 1.876360 -0.229738
4 NaN NaN
In [8]: df.fillna(0)
Out[8]:
0 1
0 0.000000 0.000000
1 -0.494375 0.570994
2 0.000000 0.000000
3 1.876360 -0.229738
4 0...
How to update gradle in android studio?
...Official links
Version Compatibility
Migrate to Android Plugin for Gradle 3.0.0
Find out the latest version of Gradle
Info about the Gradle Wrapper
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Append a NumPy array to a NumPy array
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234
In [1]: import numpy as np
In [2]: a = np.array([[1, 2, 3], [4, 5, 6]])
In [3]: b = np.array(...
Python matplotlib multiple bars
...ime.datetime(2011, 1, 6, 0, 0)
]
x = date2num(x)
y = [4, 9, 2]
z = [1, 2, 3]
k = [11, 12, 13]
ax = plt.subplot(111)
ax.bar(x-0.2, y, width=0.2, color='b', align='center')
ax.bar(x, z, width=0.2, color='g', align='center')
ax.bar(x+0.2, k, width=0.2, color='r', align='center')
ax.xaxis_date()
plt....
What is the preferred/idiomatic way to insert into a map?
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edited Nov 26 '10 at 18:37
user229044♦
202k3535 gold badges298298 silver badges309309 bronze badges
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Regex to validate date format dd/mm/yyyy
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336
The regex you pasted does not validate leap years correctly, but there is one that does in the...
dplyr summarise: Equivalent of “.drop=FALSE” to keep groups with zero length in output
....drop argument that does just what you asked for:
df = data.frame(a=rep(1:3,4), b=rep(1:2,6))
df$b = factor(df$b, levels=1:3)
df %>%
group_by(b, .drop=FALSE) %>%
summarise(count_a=length(a))
#> # A tibble: 3 x 2
#> b count_a
#> <fct> <int>
#> 1 1 ...
while (1) vs. while(True) — Why is there a difference (in python 2 bytecode)?
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3 Answers
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Accessing items in an collections.OrderedDict by index
...oo', 'python')
>>> d.items()[1]
('bar', 'spam')
Note for Python 3.X
dict.items would return an iterable dict view object rather than a list. We need to wrap the call onto a list in order to make the indexing possible
>>> items = list(d.items())
>>> items
[('foo', 'pyth...