基于切片更新 pandas 数据帧？

Question

我已经看到 - 但我找不到适合我的用例的答案。

考虑这段代码，其中我的起始 table 包含“通道”和“值”列：

import sys
if sys.version_info[0] < 3:
    from StringIO import StringIO
else:
    from io import StringIO

import pandas as pd

TESTDATA = StringIO("""channel,value
A,10
A,11
A,12
A,13
B,20
B,22
B,24
B,26
B,28
C,100
C,105
C,110
C,115
C,120
C,125
C,130
""")

mychans = ["A", "B", "C"]

df = pd.read_csv(TESTDATA)
df.insert (2, "value_rel", df["value"] - df["value"][0])

print("Starting:")
print(df.head())

for tchan in mychans:
  this_ch_data = df[df["channel"]==tchan]
  df.loc[this_ch_data.index, "value_rel"] = this_ch_data["value"] - this_ch_data["value"][0]

最后，我想获得相同的 table 和一个额外的“value_rel”列，该列将显示相对于该通道中第一个值的值（切片）；即：

A, 10, 0
A, 11, 1
A, 12, 2
A, 13, 3
B, 20, 0
B, 22, 2
B, 24, 4
B, 26, 6
B, 28, 8
C,100, 0
C,105, 5
...

如果我只是在 for 循环中使用 this_ch_data["value_rel"] = this_ch_data["value"] - this_ch_data["value"][0]，我会得到“试图在 DataFrame 的切片副本上设置一个值"，这是有道理的。

然而，当运行代码时，我得到：

$ python3 test1.py
Starting:
  channel  value  value_rel
0       A     10          0
1       A     11          1
2       A     12          2
3       A     13          3
4       B     20         10
Traceback (most recent call last):
  File "C:/msys64/mingw64/lib/python3.9/site-packages/pandas/core/indexes/base.py", line 3361, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas/_libs/index.pyx", line 76, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 108, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 2131, in pandas._libs.hashtable.Int64HashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 2140, in pandas._libs.hashtable.Int64HashTable.get_item
KeyError: 0

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\msys64\tmp\test1.py", line 38, in <module>
    df.loc[this_ch_data.index, "value_rel"] = this_ch_data["value"] - this_ch_data["value"][0]
  File "C:/msys64/mingw64/lib/python3.9/site-packages/pandas/core/series.py", line 942, in __getitem__
    return self._get_value(key)
  File "C:/msys64/mingw64/lib/python3.9/site-packages/pandas/core/series.py", line 1051, in _get_value
    loc = self.index.get_loc(label)
  File "C:/msys64/mingw64/lib/python3.9/site-packages/pandas/core/indexes/base.py", line 3363, in get_loc
    raise KeyError(key) from err
KeyError: 0

那么，我如何根据对同一 DataFrame 的（复制的）切片进行的计算来更新此 DataFrame？

Answer 1

您需要使用iloc，因为索引号0不存在于所有tchan。

for tchan in mychans:
  this_ch_data = df[df["channel"]==tchan]
  df.loc[this_ch_data.index, "value_rel"] = \
         this_ch_data["value"] - this_ch_data["value"].iloc[0]

也就是说，groupby.transform 和 first 是很好的用例。所以不需要循环，你可以做

df['value_rel'] = df['value'] - df.groupby('channel')['value'].transform('first')

Answer 2

您可以应用自定义函数将通道组减去组的第一个值。

df['value_rel'] = df.groupby('channel')['value'].apply(lambda x: x - x.iloc[0])
print(df)

# Output:
   channel  value  value_rel
0        A     10          0
1        A     11          1
2        A     12          2
3        A     13          3
4        B     20          0
5        B     22          2
6        B     24          4
7        B     26          6
8        B     28          8
9        C    100          0
10       C    105          5
11       C    110         10
12       C    115         15
13       C    120         20
14       C    125         25
15       C    130         30

基于切片更新 pandas 数据帧？

Update pandas dataframe based on slice?

python

pandas

dataframe

slice