英文:
using groupby on DataFrame in Pandas
问题
import pandas as pd
df = pd.read_csv(r"C:\Users\Ouis AL-Hetar\Documents\TestEmployeeTable1.csv")
sal = df.groupby("Department")["Salary"].sum().reset_index()
sal.columns = ["Department", "Sum_of_salary"]
print(sal)
英文:
import pandas as pd
df = pd.read_csv(r"C:\Users\Ouis AL-Hetar\Documents\TestEmployeeTable1.csv")
sal= df.groupby("Department").sum("Salary").reset_index()
sal.columns=["Dapartment","Sum_of_salary"]
print(sal)
when i treid run this code ir raise an Error:
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i have tried print head() for checking if there is any errors in the names of columns :
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but i note any error
i hope someone who knows what's the problem help me ,
sorry for my discusting English
答案1
得分: 1
CSV文件的默认分隔符是“，”。在您的情况下，分隔符似乎是分号而不是逗号，因此您需要将sep=";"作为pd.read_csv的参数来正确读取您的文件：
# 在这里 --v
df = pd.read_csv("TestEmployeeTable1.csv", sep=";")
但是，您需要修改您的其余代码：
sal = df.groupby("Department", as_index=False)["Salary"].sum()
sal.columns = ["Department", "Sum_of_salary"]
# 或者
sal = (df.groupby("Department", as_index=False)
.agg(Sum_of_salary=("Salary", "sum")))
英文:
The default separator of CSV file is ,. In your case, it seems the separator is a semicolon and not a comma so you need to set sep=";" as parameter of pd.read_csv to correctly read your file:
# HERE --v
df = pd.read_csv("TestEmployeeTable1.csv", sep=";")
However, you have to modify the rest of your code:
sal = df.groupby("Department", as_index=False)["Salary"].sum()
sal.columns = ["Department", "Sum_of_salary"]
# OR
sal = (df.groupby("Department", as_index=False)
.agg(Sum_of_salary=("Salary", "sum")))
答案2
得分: 0
pandas.DataFrame.groupby()方法与一般的DataFrame方法略有不同，因为groupby方法不会直接返回一个DataFrame或Series，这意味着它允许我们在抽象意义上将DataFrame拆分为组，但实际上并没有进行任何计算，直到在Groupby对象上调用函数。
另外要记住，groupby函数遵循（拆分-应用-合并）的过程：拆分DataFrame-应用函数-合并结果。
另外，通过groupby调用返回Groupby对象。
我认为，与其直接使用head()函数，不如使用：DataFrameGroupBy.head([n])：返回每个组的前n行。
英文:
pandas.DataFrame.groupby()method is little different from general dataframe methods , As groupby method doesnot give a DataFrame or Series in return directly meaning it allows us to split the dataframe into groups but only in an abstract sense.Nothing really get computed until a function is called on Groupby object.
Also remember a groupby function follows (split-apply-combine): Split the dataframe-apply the function-combine the result.
Also Groupby objects are returned by groupby calls
I think rather than using head() function directly
Use: DataFrameGroupBy.head([n]):Return first n rows of each group.
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