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How to find the installed pandas version
...ion__:
In [76]: import pandas as pd
In [77]: pd.__version__
Out[77]: '0.12.0-933-g281dc4e'
Pandas also provides a utility function, pd.show_versions(), which reports the version of its dependencies as well:
In [53]: pd.show_versions(as_json=False)
INSTALLED VERSIONS
------------------
commit: ...
莱昂氏unix源代码分析 PDF - 文档下载 - 清泛网 - 专注C/C++及内核技术
...源代码交叉引用列表 9
第一部分 初始化、进程初始化 25
第二部分 陷入、中断、系统调用和
进程管理 75
第三部分 程序交换、基本输入/输出、
块设备 109
第四部分 文件和目录、文件系统、...
Jasmine.js comparing arrays
... {
it('passes if arrays are equal', function() {
var arr = [1, 2, 3];
expect(arr).toEqual([1, 2, 3]);
});
});
Just for information:
toBe() versus toEqual(): toEqual() checks equivalence. toBe(), on the
other hand, makes sure that they're the exact same object.
...
How to remove specific elements in a numpy array
...index)
For your specific question:
import numpy as np
a = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
index = [2, 3, 6]
new_a = np.delete(a, index)
print(new_a) #Prints `[1, 2, 5, 6, 8, 9]`
Note that numpy.delete() returns a new array since array scalars are immutable, similar to strings in Python...
Extract elements of list at odd positions
...
232
Solution
Yes, you can:
l = L[1::2]
And this is all. The result will contain the elements p...
/usr/lib/libstdc++.so.6: version `GLIBCXX_3.4.15' not found
...
answered Mar 7 '11 at 6:20
ChrisChris
6,42377 gold badges3636 silver badges5252 bronze badges
...
How to group dataframe rows into list in pandas groupby?
...
12 Answers
12
Active
...
How can I do DNS lookups in Python, including referring to /etc/hosts?
... |
edited Mar 7 '19 at 22:59
Justin M. Keyes
5,57011 gold badge2727 silver badges5656 bronze badges
a...
Filter rows which contain a certain string
...
263
The answer to the question was already posted by the @latemail in the comments above. You can ...
How to get the first column of a pandas DataFrame as a Series?
...>>> import pandas as pd
>>> df = pd.DataFrame({'x' : [1, 2, 3, 4], 'y' : [4, 5, 6, 7]})
>>> df
x y
0 1 4
1 2 5
2 3 6
3 4 7
>>> s = df.ix[:,0]
>>> type(s)
<class 'pandas.core.series.Series'>
>>>
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