pandas 熊猫计算每个范围之间的值的数量
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Pandas calculate number of values between each range
提问by AZhao
I want to find counts of my data between certain custom ranges.
我想在某些自定义范围之间查找我的数据计数。
Say I have some data:
说我有一些数据：
import random
my_randoms = random.sample(xrange(100), 10)
test = pd.DataFrame(my_randoms,columns = ["x"])
How can I produce a data frame that shows the number of values between different ranges? For example, say I want to see how many values occur between 0-19, 20-39, 40-59, 60-79, 80-100. The output dataframe will have one column with those ranges, another with the counts.
如何生成显示不同范围之间值数量的数据框？例如，假设我想查看在 0-19、20-39、40-59、60-79、80-100 之间出现了多少个值。输出数据帧将有一列包含这些范围，另一列包含计数。
I can think of some ugly approaches that involve use of .apply to get a new column list saying which value they are between (and then doing a groupby), but I suspect pandas has a cleaner way lurking about.
我可以想到一些丑陋的方法，这些方法涉及使用 .apply 来获取一个新的列列表，说明它们之间的值（然后进行 groupby），但我怀疑 pandas 有一种更干净的方法潜伏。
采纳答案by AZhao
Per Jarad's link to that other question:
根据 Jarad 对另一个问题的链接：
test.groupby(pd.cut(test['x'], np.arange(0,100,20))).count()
回答by Gregory Kuhn
there's probably a better way. I'm only new to pandas myself but how about this for the moment:
可能有更好的方法。我自己只是Pandas的新手，但现在如何：
test.query(test.x.isin(range(20)))
回答by thekingofkings
pandas and numpy allow boolean index, is this an ugly approach?
pandas 和 numpy 允许boolean index，这是一种丑陋的方法吗？
ranges = [ (0,19), (20, 39), (40, 69) ...]
cnt = []
for range in ranges:
tmp = ranges[(ranges['x'] > range[0]) & (range['x'] <= range[1]) ]
cnt.append( len(tmp) )
回答by thekingofkings
You can use the numpy.histrogramfunction.
您可以使用该numpy.histrogram功能。
import numpy as np
series = [0, 20, 40, ...]
count, bin_edge = np.histogram( bins = series )
According to numpy.histogram, if binsis a sequence, it defines the bin edges, including the rightmost edge, allowing for non-uniform bin widths.
根据numpy.histogram，如果bins是一个序列，它定义了 bin 边缘，包括最右边的边缘，允许不均匀的 bin 宽度。
