Python Pandas：使用范围内的随机整数在 df 中创建新列
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Pandas: create new column in df with random integers from range
提问by screechOwl
I have a pandas data frame with 50k rows. I'm trying to add a new column that is a randomly generated integer from 1 to 5.
我有一个包含 50k 行的 Pandas 数据框。我正在尝试添加一个新列，它是一个从 1 到 5 的随机生成的整数。
If I want 50k random numbers I'd use:
如果我想要 50k 个随机数，我会使用：
df1['randNumCol'] = random.sample(xrange(50000), len(df1))
but for this I'm not sure how to do it.
但为此，我不知道该怎么做。
Side note in R, I'd do:
R 中的旁注，我会这样做：
sample(1:5, 50000, replace = TRUE)
Any suggestions?
有什么建议？
采纳答案by Matt
One solution is to use numpy.random.randint:
一种解决方案是使用numpy.random.randint：
import numpy as np
df1['randNumCol'] = np.random.randint(1, 6, df1.shape[0])
Or if the numbers are non-consecutive (albeit slower), you can use this:
或者，如果数字不连续（虽然速度较慢），您可以使用：
df1['randNumCol'] = np.random.choice([1, 9, 20], df1.shape[0])
In order to make the results reproducible you can set the seed with numpy.random.seed(e.g. np.random.seed(42))
为了使结果可重复，您可以使用numpy.random.seed（例如np.random.seed(42)）设置种子
回答by smci
To add a column of random integers, use randint(low, high, size). There's no need to waste memory allocating range(low, high); that could be a lot of memory if highis large.
要添加一列随机整数，请使用randint(low, high, size)。没有必要浪费内存分配range(low, high)；如果很大，那可能是很多内存high。
df1['randNumCol'] = np.random.randint(0,5, size=len(df1))
(Note also that when we're just adding a single column, sizeis just an integer. In general if we want to generate an array/dataframe of randint()s, size can be a tuple, as in Pandas: How to create a data frame of random integers?)
（还要注意，当我们只添加一列时，size它只是一个整数。一般来说，如果我们想生成一个数组/数据帧randint()s，大小可以是一个元组，如Pandas: How to create a data frame of random整数？）
