pd.drop() 메서드

Pandas.DataFrame.drop

• 프로젝트를 진행중에 아래와 같은 코드를 만났다.
  train.drop([“PassengerId”], axis = 1, inplace = True)

• 자꾸 에러가 나길래, 공부를 좀 해봤다.

• 출처 : https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop.html

• DataFrame.drop(labels=None, axis=0, index=None, columns=Nome, level=None, inplace=False, errors=’raise’)

• Drop은 행과 열로부터 레이블들을 지정한다.

• 레이블 이름과 대응되는 축을 지정해줌으로써 행과 열을 지운다.

• 또는 직접적인 인덱스나 열 이름을들 지정해줌으로써 행과 열을 지운다.

• 다중 인덱스(multi-index)를 사용할 경우 등급을 지정해줌으로써 다른 등급의 레이블도 지울 수 있다.

Parameters

labels

• single label or list-like
• 인덱스 또는 열 레이블을 지운다.
• 튜플은 single label 취급한다. list로 취급하지 않는다.

axis

• 0 or ‘index : 인덱스 자체를 지운다.
• 1 or ‘columns’ : 열 자체를 지운다.
• default는 0

index

• single label or list-like
• axis를 지정해주는 것 대신에

columns

• single label or list-like
• axis를 지정해주는 것 대신에
• 아래 예제에서 확인하자.

level

• int or level name, optional
• 다중인덱스(multiindex)의 경우, 레이블들이 있는 단계가 지워진다

inplace

• bool
• default는 False
• False라면, 복사를 반환하고
• True라면, 덮어씌우고 아무것도 반환하지 않는다.

errors

• ‘ignore’, ‘raise’
• default는 ‘raise’
• ‘ignore’를 넣어주면 에러를 막아주고, 존재하는 레이블만 지워준다.

예제

• 아래 데이터프레임이 있다.
• 아래 데이터프레임에는 name, price, rating, category 칼럼이 있다.

import pandas as pd
df = pd.DataFrame(
    {'name': ['coffee', 'tea', 'juice', 'milk', 'ade'],
     'price': [3000, 4000, 5000, 2000, 5000],
     'rating': [4, 3.5, 3.7, 3, 2],
     'category': [1,2,3,4,4]})
display(df) 

	name	price	rating	category
0	coffee	3000	4.0	1
1	tea	4000	3.5	2
2	juice	5000	3.7	3
3	milk	2000	3.0	4
4	ade	5000	2.0	4

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-03f7980f-018b-4feb-b381-386855cfd372 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-03f7980f-018b-4feb-b381-386855cfd372');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• 여기서 category 칼럼을 지워보자

df.drop(columns = ['category'])

	name	price	rating
0	coffee	3000	4.0
1	tea	4000	3.5
2	juice	5000	3.7
3	milk	2000	3.0
4	ade	5000	2.0

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-65c3339a-f6d5-470a-96a2-5b43242329b2 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-65c3339a-f6d5-470a-96a2-5b43242329b2');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• 2개 이상의 칼럼을 지울 때는?

df.drop(columns=['category', 'rating'])

	name	price
0	coffee	3000
1	tea	4000
2	juice	5000
3	milk	2000
4	ade	5000

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-5efa99d7-8bc7-4ac8-a90e-fbd405eaa342 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-5efa99d7-8bc7-4ac8-a90e-fbd405eaa342');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

칼럼을 삭제하는 다른 방법

• 필요한 칼럼만 불러오기

df[['name', 'rating']]

	name	rating
0	coffee	4.0
1	tea	3.5
2	juice	3.7
3	milk	3.0
4	ade	2.0

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-2a44dfa2-7d6c-4c48-bfa6-7969303817c5 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-2a44dfa2-7d6c-4c48-bfa6-7969303817c5');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

inplace = True

• drop() 메서드에 매개변수를 추가해보자.
• 비교를 위해 먼저, inplace = True를 쓰지 말고 코드를 실행해보자

df.drop(columns=['category'])

	name	price	rating
0	coffee	3000	4.0
1	tea	4000	3.5
2	juice	5000	3.7
3	milk	2000	3.0
4	ade	5000	2.0

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-5086c77d-5667-4bb0-a196-a74b3665357c button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-5086c77d-5667-4bb0-a196-a74b3665357c');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• category 칼럼이 아주 잘 지워졌다.
• 여기서 다시 원래 데이터프레임을 불러온다면,

display(df)

	name	price	rating	category
0	coffee	3000	4.0	1
1	tea	4000	3.5	2
2	juice	5000	3.7	3
3	milk	2000	3.0	4
4	ade	5000	2.0	4

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-b24808c0-5065-4c8c-9397-263a4a522c43 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-b24808c0-5065-4c8c-9397-263a4a522c43');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• category 칼럼이 다시 나타나는 것을 볼 수 있다.
• 별도로 df라는 객체에 저장을 안해주었기 때문이다.

inplace 변수를 사용

df.drop(columns=['category'], inplace=True)
display(df)

	name	price	rating
0	coffee	3000	4.0
1	tea	4000	3.5
2	juice	5000	3.7
3	milk	2000	3.0
4	ade	5000	2.0

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-6f6d9f85-c19c-465d-ae27-10140142fe5d button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-6f6d9f85-c19c-465d-ae27-10140142fe5d');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• inplace = True는 기존 데이터프레임에 덮어 씌우겠다는 것이다. 따로 저장하는 수고로움을 덜어주는 매개변수인 것이다.

다른 예제

import numpy as np
df = pd.DataFrame(np.arange(12).reshape(3, 4),
                  columns=['A', 'B', 'C', 'D'])
df

	A	B	C	D
0	0	1	2	3
1	4	5	6	7
2	8	9	10	11

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-8a517d47-71f1-4d40-a5fd-3060a7999df2 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-8a517d47-71f1-4d40-a5fd-3060a7999df2');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

열 지우기

• axis = 1

# axis=1 -> 열 단위로 지워라
df.drop(['B', 'C'], axis=1)

	A	D
0	0	3
1	4	7
2	8	11

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-8e52a252-c610-46b6-91da-1dd04e7d231a button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-8e52a252-c610-46b6-91da-1dd04e7d231a');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• axis 매개변수 대신에 columns 매개변수를 넣어줘도 동일하다.

df.drop(columns=['B', 'C'])

	A	D
0	0	3
1	4	7
2	8	11

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-a08dbce1-fcde-4c84-b9e8-c185688bcff1 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-a08dbce1-fcde-4c84-b9e8-c185688bcff1');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

행 지우기

• 인덱스를 통한 방법

df.drop([0, 1])

	A	B	C	D
2	8	9	10	11

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-6b39b6e6-43b6-4a88-b4a0-09c28594ead1 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-6b39b6e6-43b6-4a88-b4a0-09c28594ead1');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

다중 인덱스로 열이나 행 지우기

midx = pd.MultiIndex(levels=[['lama', 'cow', 'falcon'],
                             ['speed', 'weight', 'length']],
                     codes=[[0, 0, 0, 1, 1, 1, 2, 2, 2],
                            [0, 1, 2, 0, 1, 2, 0, 1, 2]])
df = pd.DataFrame(index=midx, columns=['big', 'small'],
                  data=[[45, 30], [200, 100], [1.5, 1], [30, 20],
                        [250, 150], [1.5, 0.8], [320, 250],
                        [1, 0.8], [0.3, 0.2]])
df

		big	small
lama	speed	45.0	30.0
	weight	200.0	100.0
	length	1.5	1.0
cow	speed	30.0	20.0
	weight	250.0	150.0
	length	1.5	0.8
falcon	speed	320.0	250.0
	weight	1.0	0.8
	length	0.3	0.2

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-9c8e9bb3-86d7-4bfe-8187-b190cbaa4ac9 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-9c8e9bb3-86d7-4bfe-8187-b190cbaa4ac9');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• 위 데이터 프레임에서 ‘falcon’의 ‘weight’를 지우기

df.drop(index=('falcon', 'weight'))

		big	small
lama	speed	45.0	30.0
	weight	200.0	100.0
	length	1.5	1.0
cow	speed	30.0	20.0
	weight	250.0	150.0
	length	1.5	0.8
falcon	speed	320.0	250.0
	length	0.3	0.2

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-fc708903-fd28-49e1-8747-c17b53c42861 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-fc708903-fd28-49e1-8747-c17b53c42861');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• ‘cow’ 인덱스와 ‘small’ 열 지우기

df.drop(index='cow', columns='small')

		big
lama	speed	45.0
	weight	200.0
	length	1.5
falcon	speed	320.0
	weight	1.0
	length	0.3

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-0268e32a-e810-4e90-9aa7-ee48a261a652 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-0268e32a-e810-4e90-9aa7-ee48a261a652');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

• 모든 인덱스에 ‘length’ 지우기

df.drop(index='length', level=1)

		big	small
lama	speed	45.0	30.0
	weight	200.0	100.0
cow	speed	30.0	20.0
	weight	250.0	150.0
falcon	speed	320.0	250.0
	weight	1.0	0.8

<svg xmlns=”http://www.w3.org/2000/svg" height=”24px”viewBox=”0 0 24 24”
width=”24px”>

  <script>
    const buttonEl =
      document.querySelector('#df-66624418-0a6c-42d1-8fb4-aa14716959d2 button.colab-df-convert');
    buttonEl.style.display =
      google.colab.kernel.accessAllowed ? 'block' : 'none';

    async function convertToInteractive(key) {
      const element = document.querySelector('#df-66624418-0a6c-42d1-8fb4-aa14716959d2');
      const dataTable =
        await google.colab.kernel.invokeFunction('convertToInteractive',
                                                 [key], {});
      if (!dataTable) return;

      const docLinkHtml = 'Like what you see? Visit the ' +
        '<a target="_blank" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'
        + ' to learn more about interactive tables.';
      element.innerHTML = '';
      dataTable['output_type'] = 'display_data';
      await google.colab.output.renderOutput(dataTable, element);
      const docLink = document.createElement('div');
      docLink.innerHTML = docLinkHtml;
      element.appendChild(docLink);
    }
  </script>
</div>

pd.drop() 메서드

http://griotold.github.io/2022/04/01/pd_drop()/

Author

HS

Posted on

2022-04-01

Updated on

2022-04-01

Licensed under

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