pandas 将函数应用于两列熊猫数据框以获得两个新列
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Applying a function to two columns of pandas dataframe to get two new columns
提问by ahoosh
I have a pandas data frame with columns Longitudeand Latitude. I'd like to get Xand Yfrom them. There is a function in utmcalled from_latlonthat does this. It receives Latitudeand Longitudeand gives [X,Y]. Here's what I do:
我有一个带有列Longitude和Latitude. 我想获得X并Y从他们。在utm调用from_latlon中有一个函数可以做到这一点。它接收Latitude和Longitude并给出[X,Y]。这是我所做的：
def get_X(row):
return utm.from_latlon(row['Latitude'], row['Longitude'])[0]
def get_Y(row):
return utm.from_latlon(row['Latitude'], row['Longitude'])[1]
df['X'] = df.apply(get_X, axis=1)
df['Y'] = df.apply(get_Y, axis=1)
I'd like to define a function get_XYand apply from_latlonjust one time to save time. I took a look at here, hereand herebut I could not find a way to make two columns with one applyfunction. Thanks.
我想定义一个函数get_XY并from_latlon只应用一次以节省时间。我查看了here、here和here，但我找不到用一个apply函数创建两列的方法。谢谢。
回答by BrenBarn
You can return a list from your function:
您可以从您的函数返回一个列表：
d = pandas.DataFrame({
"A": [1, 2, 3, 4, 5],
"B": [8, 88, 0, -8, -88]
})
def foo(row):
return [row["A"]+row["B"], row["A"]-row["B"]]
>>> d.apply(foo, axis=1)
A B
0 9 -7
1 90 -86
2 3 3
3 -4 12
4 -83 93
You can also return a Series. This lets you specify the column names of the return value:
您也可以返回一个系列。这使您可以指定返回值的列名：
def foo(row):
return pandas.Series({"X": row["A"]+row["B"], "Y": row["A"]-row["B"]})
>>> d.apply(foo, axis=1)
X Y
0 9 -7
1 90 -86
2 3 3
3 -4 12
4 -83 93
回答by RufusVS
I merged a couple of the answers from a similar thread and now have a generic multi-column in, multi-column out template I use in Jupyter/pandas:
我合并了来自类似线程的几个答案，现在有一个通用的多列输入、多列输出模板，我在 Jupyter/pandas 中使用：
# plain old function doesn't know about rows/columns, it just does its job.
def my_func(arg1,arg2):
return arg1+arg2, arg1-arg2 # return multiple responses
df['sum'],df['difference'] = zip(*df.apply(lambda x: my_func(x['first'],x['second']),axis=1))
