[英]pandas: Convert Series of DataFrames to single DataFrame
I have a pandas Series
object with each value being a DataFrame
.我有一个 pandas
Series
对象,每个值都是一个DataFrame
。 I am trying convert this into a single DataFrame
with all of the Series
values (individual DataFrame
) stacked on top of each other.我正在尝试将其转换为单个
DataFrame
,其中所有Series
值(单个DataFrame
)彼此堆叠。 How can I achieve this without a loop?我怎样才能在没有循环的情况下实现这一点?
A toy example below to generate the test object ( results
).下面的玩具示例用于生成测试对象(
results
)。
import pandas as pd
import numpy as np
numrows = 10000
def toy_function(x):
silly_sequence = np.random.uniform(10, 100, (x+1))
toy = pd.DataFrame({'ID':pd.Series(np.random.random_integers(1,20,3)),'VALUE':pd.Series((np.median(silly_sequence),np.mean(silly_sequence), np.max(silly_sequence)))})
return toy
results = pd.DataFrame({'ID':range(numrows)})['ID'].apply(toy_function)
results
is of Series
type and each element is a DataFrame
like so: results
是Series
类型,每个元素都是一个DataFrame
,如下所示:
In [1]: results[1]
Out[1]:
ID VALUE
0 17 40.035398
1 8 40.035398
2 20 66.483083
I am looking for a way to stack results[1]
, results[2]
etc. on top of each other to yield a DataFrame like this:我正在寻找一种将
results[1]
、 results[2]
等堆叠在一起以产生如下 DataFrame 的方法:
ID VALUE
0 17 40.035398
1 8 40.035398
2 20 66.483083
4 12 25.035398
5 1 25.135398
6 19 65.553083
...
Try using pd.concat
.尝试使用
pd.concat
。 At the very least, pd.concat(series.tolist())
should work.至少,
pd.concat(series.tolist())
应该可以工作。
Its default is to take a list of pandas dataframes or series and return them tacked end on end.它的默认设置是获取 pandas 数据框或系列的列表,并将它们端接返回。 http://pandas.pydata.org/pandas-docs/stable/merging.html
http://pandas.pydata.org/pandas-docs/stable/merging.html
连接结果并在这样做时忽略您的索引:
df_stacked = pd.concat([r for r in results], ignore_index=True)
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