Question

I have a dataframe that I want to apply a function that take one value and will give two values as a result. I used .apply(get_data).transpose().values to put the results to the dataframe. It worked when I had only two rows in the dataframe but didn t worked with more than two rows. I got the "Too many values to unpack (expected 2)" error.

 oil_df = pd.DataFrame({
    "Oils":["Oil 1","Oil 2","Oil 3"], 
    "Price":["","",""], 
    "Unit":["","",""]})

def get_data(oil):
    if oil == "Oil 1":
        price = 20
        unit = 50
    if oil == "Oil 2":
        price = 30
        unit = 75
    if oil == "Oil 3":
        price = 40
        unit = 100
    return(price, unit)

oil_df["Price"], oil_df["Unit"] = oil_df["Oils"].apply(get_data).transpose().values

At first, I couldn t find a way to apply the function, so I divided the function to two pieces and applied them one by one, but it took so much longer as expected. I found this way with the help of this answer. axis=1, result_type= expand is giving me "get_data() got an unexpected keyword argument axis " error, so removed that part. I m open to any suggestions to make this work or another way to apply this function to the dataframe. Thank you!

Answer 1

不知道你真心想做到这一点,但你正在转换数据,因此,你返回的阵列有3个 t子(石油1、2和3),因此其价值太多,无法包装。

如果你打算填入第二栏和第三栏,那么你就希望回到一个数据组,即每行一个系列,然后将其用作对数据组第二栏的投入。

import pandas as pd

oil_df = pd.DataFrame({
    "Oils":["Oil 1","Oil 2","Oil 3"], 
    "Price":["","",""], 
    "Unit":["","",""]})

def get_data(oil):
    if oil == "Oil 1":
        price = 20
        unit = 50
    if oil == "Oil 2":
        price = 30
        unit = 75
    if oil == "Oil 3":
        price = 40
        unit = 100
    return pd.Series([price, unit])

oil_df[[ Price ,  Unit ]] = oil_df["Oils"].apply(get_data)

oil_df

回返

    Oils    Price   Unit
0   Oil 1   20  50
1   Oil 2   30  75
2   Oil 3   40  100

本案

oil_df["Oils"].apply(get_data)

回返

    0   1
0   20  50
1   30  75
2   40  100

并将之分配给<代码>oil_df[[价格,单位]]。

Answer 2

Try loc or np.select

for column, values in [( Price , [20, 30, 40]), ( Unit , [50, 75, 100])]:
    # loc
    # oil_df.loc[oil_df[ Oils ].isin([ Oil 1 ,  Oil 2 ,  Oil 3 ]), column] = values
    # np.select
    oil_df[column] = np.select(condlist=[oil_df[ Oils ] == f Oil {i}  for i in range(1, 4)], choicelist=values)

产出

    Oils Price Unit
0  Oil 1    20   50
1  Oil 2    30   75
2  Oil 3    40  100

友情链接