How to get the difference of the max and min of the row and input as series for a dataframe?

df['range'] = df.max(axis=1) - df.min(axis=1)

If you want to specify column numbers to calculate the range:

df['range'] = df.iloc[:,col1index:col2index].max(axis=1) - df.iloc[:,col1index:col2index].min(axis=1)

Filter for only the Values column and compute the difference of the max and min per row :

boxes = df.filter(like="Value")

df["range"] = boxes.max(1) - boxes.min(1)
df

    Ind Department  Value1  Value2  Value3  Value4  range
0   1   Electronics    5       4       3       2    3
1   2   Clothing       4       3       2       1    3
2   3   Grocery        3       3       5       1    4

Same end result, but longer route, in my opinion - set the first two columns as index, get the difference of the max and min for each row, and reset the index :

(df
.set_index(["Ind", "Department"])
.assign(max_min=lambda x: x.max(1) - x.min(1))
.reset_index()
)

You can try numpy ptp

np.ptp(df.loc[:,'Value1':].values,axis=1)
array([3, 3, 4], dtype=int64)
df['range']=np.ptp(df.loc[:,'Value1':].values,axis=1)