I am learning how to write a python class and method chaining at the moment. Basically, I want a python (2.7) class that keeps my data and has (chain-able) methods that allow me to filter the data without mutating my original data. I have done some Googling and it seems like my answer might have something to do with return self, but I am not sure how to implement it such that the methods will not mutate my original data.
Let's say I have a data stored in an excel file called file as follows:
+--------+-----+-------+
| Person | Sex | Score |
+--------+-----+-------+
| A | M | 10 |
| B | F | 9 |
| C | M | 8 |
| D | F | 7 |
+--------+-----+-------+
I would like to write a class called MyData such that I can do some basic data calling and filtering.
This is what I got so far
class MyData:
def __init__ (self, file):
import pandas as pd
self.data = pd.read_excel (file)
self.Person = self.data['Person']
self.Sex = self.data['Sex']
self.Score = self.data['Score']
def male_only(self):
self.data = self.data[self.Sex=="M"]
self.Person = self.Person[self.Sex=="M"]
self.Score = self.Score[self.Sex=="M"]
self.Sex = self.Sex[self.Sex=="M"]
return self
def female_only(self):
self.data = self.data[self.Sex=="F"]
self.Person = self.Person[self.Sex=="F"]
self.Score = self.Score[self.Sex=="F"]
self.Sex = self.Sex[self.Sex=="F"]
return self
This seems to work, but sadly my original data is permanently mutated with this code. For example:
Data = MyData(file)
Data.data
>>> Data.data
Person Sex Score
0 A M 10
1 B F 9
2 C M 8
3 D F 7
Data.male_only().data
>>> Data.male_only().data
Person Sex Score
0 A M 10
2 C M 8
Data.data
>>> Data.data
Person Sex Score
0 A M 10
2 C M 8
I would like a class that returns the same answers for Data.male_only().Person and Data.Person.male_only() or for Data.male_only().data and Data.data.male_only() without permanently mutating Data.data or Data.Person.
I agree with @Demi-Lune.
I changed OP's code so that male_only() and female_only() methods always return copy of its belonging object. And I changed __init__() method because I think you don't want to call pd.read_csv() method every time creating that new object. So male_only() and female_only() method always return new object, it will no effect on other objects.
import pandas as pd
# Added for creating file on memory.
import io
csv = '''Person,Sex,Score
p1,M,1
p2,M,2
p3,M,3
p4,F,4
p5,F,5
p6,F,6'''
file = io.StringIO(csv)
class MyData:
def __init__ (self, file=None, data=None):
import pandas as pd
if file:
self.data = pd.read_csv(file)
else:
self.data = data
self.Person = self.data['Person']
self.Sex = self.data['Sex']
self.Score = self.data['Score']
def copy_d(self):
return MyData(data=self.data.copy())
def male_only(self):
d = self.copy_d()
d.data = self.data[self.Sex=="M"]
d.Person = self.Person[self.Sex=="M"]
d.Score = self.Score[self.Sex=="M"]
d.Sex = self.Sex[self.Sex=="M"]
return d
def female_only(self):
d = self.copy_d()
d.data = self.data[self.Sex=="F"]
d.Person = self.Person[self.Sex=="F"]
d.Score = self.Score[self.Sex=="F"]
d.Sex = self.Sex[self.Sex=="F"]
return d
d = MyData(file)
print(d.female_only().data)
# Person Sex Score
# 3 p4 F 4
# 4 p5 F 5
# 5 p6 F 6
print(d.male_only().data)
# Person Sex Score
# 0 p1 M 1
# 1 p2 M 2
# 2 p3 M 3
print(d.data)
# Person Sex Score
# 0 p1 M 1
# 1 p2 M 2
# 2 p3 M 3
# 3 p4 F 4
# 4 p5 F 5
# 5 p6 F 6
But if your are just using pandas.DataFrame, another approach is just using bare pandas.DataFrame. First thing is that, in most case, pandas.DataFrame object already has properties name which equals to columns name. So in fact, you don't need to define properties like Person, Sex, Score because it already exists in DataFrame object.
ie:
import pandas as pd
import numpy as np
df = pd.DataFrame(np.eye(3,3), columns=['Person', 'Sex', 'Score'])
# `df` already has these properteis.
df.Person
df.Sex
df.Score
# In [986]: df.Person
# Out[986]:
# 0 1.0
# 1 0.0
# 2 0.0
# Name: Person, dtype: float64
# In [987]: df.Sex
# Out[987]:
# 0 0.0
# 1 1.0
# 2 0.0
# Name: Sex, dtype: float64
# In [988]: df.Score
# Out[988]:
# 0 0.0
# 1 0.0
# 2 1.0
# Name: Score, dtype: float64
So, your male_only() and female_only() methods are written like following.
import pandas as pd
# Added for creating file on memory.
import io
csv = '''Person,Sex,Score
p1,M,1
p2,M,2
p3,M,3
p4,F,4
p5,F,5
p6,F,6'''
file = io.StringIO(csv)
def male_only(df):
return df[df.Sex=='M']
def female_only(df):
return df[df.Sex=='F']
df = pd.read_csv(file)
male_only(df)
# In [1034]: male_only(df)
# Out[1037]:
# Person Sex Score
# 0 p1 M 1
# 1 p2 M 2
# 2 p3 M 3
female_only(df)
# In [1038]: female_only(df)
# Out[1041]:
# Person Sex Score
# 3 p4 F 4
# 4 p5 F 5
# 5 p6 F 6
I hope it will help you.