使用来自数组元组的列构建DataFrame

Question

我正在努力构建一个基于生成的元组的值计数的DataFrame的基本任务np.unique(arr, return_counts=True),例如:

import numpy as np
import pandas as pd

np.random.seed(123)  
birds=np.random.choice(['African Swallow','Dead Parrot','Exploding Penguin'], size=int(5e4))
someTuple=np.unique(birds, return_counts = True)
someTuple
#(array(['African Swallow', 'Dead Parrot', 'Exploding Penguin'], 
#       dtype='<U17'), array([16510, 16570, 16920], dtype=int64))

首先我试过了

pd.DataFrame(list(someTuple))
# Returns this:
#                  0            1                  2
# 0  African Swallow  Dead Parrot  Exploding Penguin
# 1            16510        16570              16920

我也试过pd.DataFrame.from_records(someTuple),它返回同样的东西.

但我正在寻找的是:

#              birdType      birdCount
# 0     African Swallow          16510  
# 1         Dead Parrot          16570  
# 2   Exploding Penguin          16920

什么是正确的语法？

Answer 1

使用元组，您可以执行以下操作：

In [4]: pd.DataFrame(list(zip(*someTuple)), columns = ['Bird', 'BirdCount'])
Out[4]: 
                Bird  BirdCount
0    African Swallow      16510
1        Dead Parrot      16570
2  Exploding Penguin      16920

Answer 2

这是一个基于NumPy的解决方案，具有np.column_stack-

pd.DataFrame(np.column_stack(someTuple),columns=['birdType','birdCount'])

或np.vstack-

pd.DataFrame(np.vstack(someTuple).T,columns=['birdType','birdCount'])

基准测试np.transpose，np.column_stack以及np.vstack将1D数组放样 到列中以形成2D数组-

In [54]: tup1 = (np.random.rand(1000),np.random.rand(1000))

In [55]: %timeit np.transpose(tup1)
100000 loops, best of 3: 15.9 µs per loop

In [56]: %timeit np.column_stack(tup1)
100000 loops, best of 3: 11 µs per loop

In [57]: %timeit np.vstack(tup1).T
100000 loops, best of 3: 14.1 µs per loop

Answer 3

创建字典

pd.DataFrame(dict(birdType=someTuple[0], birdCount=someTuple[1]))