在 pandas 中将行拆分为多行

本文介绍了在 pandas 中将行拆分为多行的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我有一个DataFrame，其格式如下(简化)

I have a DataFrame with a format like this (simplified)

a b 43 a c 22

我希望通过以下方式对此进行分解.

I would like this to be split up in the following way.

a b 20 a b 20 a b 1 a b 1 a b 1 a c 20 a c 1 a c 1

在这里，行数除以20，然后剩下的行数也一样.我有一个解决方案，基本上可以对行进行迭代并填充字典，然后可以将其转换回Dataframe，但我想知道是否有更好的解决方案.

Where I have as many rows as the number divides by 20, and then as many rows as the remainder. I have a solution that basically iterates over the rows and fills up a dictionary which can then be converted back to Dataframe but I was wondering if there is a better solution.

推荐答案

您可以先对模数使用地板分位数，然后通过constructor与DataFrame. org/doc/numpy/reference/generated/numpy.repeat.html"rel =" nofollow noreferrer> numpy.repeat .

You can use floor divison with modulo first and then create new DataFrame by constructor with numpy.repeat.

最近需要 numpy.concatenate ，其中list comprehension表示C:

a,b = df.C // 20, df.C % 20 #print (a, b) cols = ['A','B'] df = pd.DataFrame({x: np.repeat(df[x], a + b) for x in cols}) df['C'] = np.concatenate([[20] * x + [1] * y for x,y in zip(a,b)]) print (df) A B C 0 a b 20 0 a b 20 0 a b 1 0 a b 1 0 a b 1 1 a c 20 1 a c 1 1 a c 1