아미(아름다운미소)

sudo chmod 666 /var/run/docker.sock

df['bool_col'] = df['bool_col'].astype(str).str.lower().eq('true')df['bool_col'] = df['bool_col'].fillna(False).astype(str).str.lower().eq('true')df['bool_col'] = df['bool_col'].map(lambda x: x is True)

sveltekit 프로젝트 생성npx sv create my-sveltekit-appcd my-sveltekit-app adapter-node 설치(build폴더 생성)npm install -D @sveltejs/adapter-nodesvelte.config.js 수정import adapter from '@sveltejs/adapter-node';import { vitePreprocess } from '@sveltejs/vite-plugin-svelte';/** @type {import('@sveltejs/kit').Config} */const config = { preprocess: vitePreprocess(), kit: { adapter: adapter({ out: 'build' }) // bui..

import pandas as pd# 초기 데이터프레임 생성df = pd.DataFrame({'ccc': [1, 2, 3]})# 조건에 따라 추가할 열 정의new_columns = {}if df['ccc'].max() > 2: new_columns['aaa'] = df['ccc']if df['ccc'].min() ccc aaa bbb0 1 1.0 21 2 2.0 42 3 3.0 6

import pandas as pd# 예시 데이터프레임 생성data = { 'a': ['value1_value2', '', 'value3_value4', 'value5_value6'], 'b': [1, 2, 3, 4]}df = pd.DataFrame(data)# a 컬럼이 빈 문자열이 아닐 경우 _ 기준으로 split하고 첫 번째 값 사용df['first_value'] = df['a'].apply(lambda x: x.split('_')[0] if x else None)print(df)

import pandas as pd# 예시 데이터프레임 생성data1 = {'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]}data2 = {'a': [2, 3, 4], 'b': [5, 6, 7], 'c': [8, 9, 10]}df = pd.DataFrame(data1)df2 = pd.DataFrame(data2)# df2에만 있는 값 찾기result = df2[~df2.set_index(['a', 'b', 'c']).index.isin(df.set_index(['a', 'b', 'c']).index)]print(result)

import pandas as pd# 예시 데이터프레임 생성data = { 'A': [1, 2, 'three', 4], 'B': [True, False, 7.2, 'eight'], 'C': [9, 10, 11, 12]}df = pd.DataFrame(data)# 데이터 타입 확인print("데이터 타입:")print(df.dtypes)# 타입이 다른 행 찾기non_string_A = df[~df['A'].apply(lambda x: isinstance(x, str))]non_int_C = df[~df['C'].apply(lambda x: isinstance(x, int))]non_bool_B = df[~df['B'].apply(lambda x: isinstance(x, bool))]pri..

sql case whenSELECT 이름, 성적, 출석률, CASE WHEN 성적 >= 90 AND 출석률 >= 90 THEN 'A' WHEN 성적 >= 80 AND 출석률 >= 80 THEN 'B' WHEN 성적 >= 70 AND 출석률 >= 70 THEN 'C' WHEN 성적 >= 60 AND 출석률 >= 60 THEN 'D' ELSE 'F' END AS 등급FROM 학생;np.whereimport pandas as pdimport numpy as np# 샘플 DataFrame 생성data = { '이름': ['학생1', '학생2', '학생3', '학생4', '학생..

import pandas as pddef fn_df(dict_df_types, df) -> pd.DataFrame: list_int = [k_ for (k_, v_) in dict_df_types.items() if (v_ != 'string') and (v_ != 'boolean') and (k_ in df.columns.to_list())] list_str = [k_ for (k_, v_) in dict_df_types.items() if (v_ == 'string') and (k_ in df.columns.to_list())] list_bool = [k_ for (k_, v_) in dict_df_types.items() if (v_ == 'boolean') and (k_ in df..

rm -Rf /Applications/Android\ Studio.apprm -Rf ~/Library/Preferences/AndroidStudio*rm -Rf ~/Library/Preferences/com.google.android.*rm -Rf ~/Library/Preferences/com.android.*rm -Rf ~/Library/Application\ Support/AndroidStudio*rm -Rf ~/Library/Logs/AndroidStudio*rm -Rf ~/Library/Caches/AndroidStudio*rm -Rf ~/.AndroidStudio*rm -Rf ~/Library/Application\ Support/Google/AndroidStudio*https://stackov..