将元组添加到 Pandas 数据帧的特定单元格
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Add a tuple to a specific cell of a pandas dataframe
提问by user1718097
Just when I thought I was getting the hang of Python and Pandas, another seemingly simple issue crops up. I want to add tuples to specific cells of a pandas dataframe. These tuples need to be calculated on-the-fly based on the contents of other cells in the dataframe - in other words, I can't easily calculate all tuples in advance and add them as a single array.
就在我以为我已经掌握了 Python 和 Pandas 的窍门时，另一个看似简单的问题突然出现了。我想将元组添加到 Pandas 数据帧的特定单元格。这些元组需要根据数据帧中其他单元格的内容即时计算 - 换句话说，我无法轻松提前计算所有元组并将它们添加为单个数组。
As an example, I define a dataframe with some data and add a couple of empty columns:
例如，我定义了一个包含一些数据的数据框并添加了几个空列：
import pandas as pd
import bumpy as np
tempDF = pd.DataFrame({'miscdata': [1.2,3.2,4.1,2.3,3.3,2.5,4.3,2.5,2.2,4.2]})
tempDF['newValue'] = np.nan
tempDF['newTuple'] = np.nan
I can scroll through each cell of the 'newValue' column and add an integer value without problems:
我可以滚动浏览“newValue”列的每个单元格并添加一个整数值而不会出现问题：
anyOldValue = 3.5
for i in range(10):
tempDF.ix[(i,'newValue')] = anyOldValue
print tempDF
However, if I try to add a tuple I get an error message:
但是，如果我尝试添加元组，则会收到一条错误消息：
anyOldTuple = (2.3,4.5)
for i in range(10):
tempDF.ix[(i,'newTuple')] = anyOldTuple
print tempDF
I've received several error messages including:
我收到了几条错误消息，包括：
ValueError: Must have equal len keys and value when setting with an ndarray
…and…
…和…
ValueError: setting an array element with a sequence.
I'm sure I've seen data frames with tuples (or lists) in the cells - haven't I? Any suggestions how to get this code working would be much appreciated.
我确定我在单元格中看到过带有元组（或列表）的数据框 - 不是吗？任何有关如何使此代码工作的建议将不胜感激。
回答by elyase
You can use set_value:
您可以使用set_value：
tempDF.set_value(i,'newTuple', anyOldTuple)
Also make sure that the column is not a float column, for example:
还要确保该列不是浮动列，例如：
tempDF['newTuple'] = 's' # or set the dtype
otherwise you will get an error.
否则你会得到一个错误。
回答by J.Melody
set_value is deprecated.
set_value 已弃用。
you can just use .at[] or iat[]
你可以只使用 .at[] 或 iat[]
e.g. some_df.at[ idx, col_name] = any_tuple
例如 some_df.at[ idx, col_name] = any_tuple
回答by Markus Dutschke
As J.Melodypointed out, .at[]and .iat[]can be used to assign a tuple to a cell, if the dtype of the column is object.
正如J.Melody指出的，.at[]并且.iat[]可用于一元组分配给一个小区，如果列的D型是object。
Minimal example:
最小的例子：
df initialized as:
a b c
0 0 1 2
1 3 4 5
2 6 7 8
df containing tuple:
a b c
0 0 (1, 2) 2
1 3 4 5
2 6 7 8
Code:
代码：
import numpy as np
import pandas as pd
df = pd.DataFrame(np.arange(9).reshape((3,3)), columns=list('abc'), dtype=object)
print('df initialized as:', df, sep='\n')
df.at[0,'b'] = (1,2)
print()
print('df containing tuple:', df, sep='\n')
Note:
笔记：
If you skip , dtype=object, you end up with
如果你跳过, dtype=object，你最终会得到
ValueError: setting an array element with a sequence.
