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Normalize data in pandas
Suppose I have a pandas data frame df :
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How to add an extra column to a NumPy array
Let’s say I have a NumPy array, a :
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Find row where values for column is maximal in a pandas DataFrame
How can I find the row for which the value of a specific column is maximal ?
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linux下iptables配置详解 - 更多技术 - 清泛网 - 专注C/C++及内核技术
linux下iptables配置详解如果你的IPTABLES基础知识还不了解,建议先去看看.开始配置我们来配置一个filter表的防火墙.(1)查看本机关于IPTABLES的设置情况[root@tp ~]...如果你的IPTABLES基础知识还不了解,建议先去看看.
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Programmatically Lighten or Darken a hex color (or rgb, and blend colors)
Here is a function I was working on to programmatically lighten or darken a hex color by a specific amount. Just pass in a string like "3F6D2A" for the color ( col ) and a base10 integer ( amt ) for the amount to lighten or darken. To darken, pass in a negative number (i.e. -20 ).
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Get statistics for each group (such as count, mean, etc) using pandas GroupBy?
I have a data frame df and I use several columns from it to groupby :
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Are list-comprehensions and functional functions faster than “for loops”?
In terms of performance in Python, is a list-comprehension, or functions like map() , filter() and reduce() faster than a for loop? Why, technically, they run in a C speed , while the for loop runs in the python virtual machine speed ?.
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Linear Regression and group by in R
I want to do a linear regression in R using the lm() function. My data is an annual time series with one field for year (22 years) and another for state (50 states). I want to fit a regression for each state so that at the end I have a vector of lm responses. I can imagine doing for loop for each ...
How to use a decimal range() step value?
Is there a way to step between 0 and 1 by 0.1?
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How to change the order of DataFrame columns?
I have the following DataFrame ( df ):
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