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[ 오류 로그 ]> pip install lanarky==0.8.6ERROR: Ignored the following yanked versions: 0.7.11ERROR: Could not find a version that satisfies the requirement lanarky==0.8.6 (from versions: 0.6.0, 0.6.1, 0.6.2, 0.6.3, 0.6.4, 0.6.5, 0.6.6, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.7.4, 0.7.5, 0.7.6, 0.7.7, 0.7.8, 0.7.9, 0.7.10, 0.7.12, 0.7.13, 0.7.14, 0.7.15, 0.7.16, 0.7.17)ERROR: No matching distribution found for..

[ 오류 로그 ] > pip install -r requirements.txt ... Building wheel for hnswlib (pyproject.toml) ... error error: subprocess-exited-with-error × Building wheel for hnswlib (pyproject.toml) did not run successfully. │ exit code: 1 ╰─> [5 lines of output] running bdist_wheel running build running build_ext building 'hnswlib' extension error: Microsoft Visual C++ 14.0 or gre..

1. Download Anaconda3Anaconda3 download url : https://www.anaconda.com/download/successLinux, Python 3.12 > 64-Bit (x86) Installer (1007.9M)https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Linux-x86_64.sh * download file name : Anaconda3-2024.06-1-Linux-x86_64.sh 2. Run terminal 3. Move Anaconda 3 download directory$ cd [download directory] (ex, download directory : ~/Download)$ cd Downlo..

>>> import pandas as pd>>> df1 = pd.read_csv('sample.csv')>>> df1.mean():1: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.Eng 83.1Math 73.7dtype: float64 [ Solve ]Select only valid columns or set numeric_only=True. >>> df1.m..

import pandas as pd df = pd.read_csv('sample.csv') df.median() or df.corr() [ Error message ] --------------------------------------------------------------------------------------------------------------------------------- :1: FutureWarning: The default value of numeric_only in DataFrame.median is deprecated. In a future version, it will default to False. In addition, specifying 'numeric_only=N..

[ CSV file read ] >>> import pandas as pd >>> df1 = pd.read_csv('sample.csv') >>> df1 StdID Middle Final 0 S01 90 95 1 S02 82 83 2 S03 80 78 3 S04 78 75 4 S05 93 91 [ 'StdID' set index ] >>> df1.set_index('StdID', inplace=True) >>> df1 Middle Final StdID S01 90 95 S02 82 83 S03 80 78 S04 78 75 S05 93 91 * inplace=True option df1.set_index('StdID', inplace=True) => df1 = df1.set_index('StdID') [ ..

import pandas as pd df = pd.read_csv('sample.csv') --------------------------------------------------------------------------- UnicodeDecodeError Traceback (most recent call last) in () ----> 1 df = pd.read_csv('sample.csv') 10 frames /usr/local/lib/python3.10/dist-packages/pandas/_libs/parsers.pyx in pandas._libs.parsers.raise_parser_error() UnicodeDecodeError: 'utf-8' codec can't decode byte 0..

[ Code ] --------------------------------------------------------------------------- import pandas as pd df1 = pd.read_csv('sample.csv') --------------------------------------------------------------------------- [ Error message ] C:\py_test> python sample.py Traceback (most recent call last): File "C:\py_test\sample.py", line 3, in df1 = pd.read_csv('sample.csv') File "C:\Python\Python39\lib\si..

1. 천 단위 숫자를 컴마(',')로 구분하기 1.1 format() 함수 사용 >>> format(1234567890, ',') '1,234,567,890' 1.2 f-string으로 문자열 포멧팅하기 >>> f'{1234567890:,}' '1,234,567,890' 2. 천 단위 숫자를 컴마(',') 제거 2.1 split(), join() 함수 이용 >>> ''.join('1,234,567,890'.split(',')) '1234567890' 2.2 replace() 함수 이용 >>> '1,234,567,890'.replace(',', '')

- Error message : ImportError: libf77blas.so.3: cannot open shared object file: No such file or directory - Solutions : $ sudo apt install libatlas-base-dev gangserver@raspberrypi:~/devel/pydev $ python BreamAndSmelt.py Traceback (most recent call last): File "/home/gangserver/devel/pydev/BreamAndSmelt.py", line 35, in from sklearn.neighbors import KNeighborsClassifier File "/usr/local/lib/pytho..