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<!DOCTYPE html> | |
<html lang="ja"> | |
<head> | |
<meta charset="UTF-8"> | |
<title>カレンダー時間選択ツール</title> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<style> | |
/* CSSコード */ | |
/* ベーススタイル */ | |
* { |
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using Pkg | |
function add_if_not_found(packages) | |
installed = [dep.name for (_, dep) in Pkg.dependencies() if dep.is_direct_dep] | |
targets = [] | |
for pkg in packages | |
pkg in installed || push!(pkg, targets) | |
end | |
isempty(targets) || Pkg.add(targets) | |
end |
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import pandas as pd | |
def coalesce(df: pd.DataFrame, *args) -> pd.Series: | |
return df[list(args)].bfill(axis=1).iloc[:, 0] |
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FROM python:3.10 | |
RUN pip install --no-cache-dir --upgrade pip && \ | |
pip install --no-cache-dir pandas==1.4.3 pyarrow==8.0.0 fastparquet==0.8.1 |
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def melt_columns(df: pd.DataFrame, sep: str="_") -> pd.DataFrame: | |
"""与えられたデータフレームの列がMultiIndexの場合にそれを非階層なIndexにして返す. | |
Arguments: | |
df (pd.DataFrame) : 列を非階層にしたいデータフレーム. | |
sep (str) : 新たな列名を作るときにセパレーターとして使われる文字列. デフォルトでは"_". | |
Return: | |
pd.DataFrame : 列名が非階層なIndexとなっているデータフレーム | |
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import time | |
import numpy as np | |
import pandas as pd | |
def np_mode(df): | |
""" | |
与えられたDataFrameの各列から最頻値を返す | |
Original: https://twitter.com/nkay/status/1328231713919496194 | |
""" |
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# julia> versioninfo() | |
# Julia Version 1.5.0 | |
# Commit 96786e22cc (2020-08-01 23:44 UTC) | |
# Platform Info: | |
# OS: macOS (x86_64-apple-darwin18.7.0) | |
# CPU: Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz | |
# WORD_SIZE: 64 | |
# LIBM: libopenlibm | |
# LLVM: libLLVM-9.0.1 (ORCJIT, skylake) |
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## Convert strings of 2-digits number have the following tricky format to an integer. | |
## Tricky format: the last digit is described as decimal, and the first digit is chosen from {1, ..., 9, A, ..., Z, a, ..., z}. | |
## The min is 0(="00") and the max is 619(="z9"). | |
## Example: "15" -> 15, "A0" -> 100, "Z9" -> 359, "a0" -> 360, "c5" -> 385 | |
def num2int(num): | |
if num.isdigit(): | |
return int(num) | |
elif num[0].isupper(): | |
return int(num[0], 36) * 10 + int(num[1]) |
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import pandas as pd | |
import jsm | |
import datetime | |
def get_historical_price(stockcode, start_date=None, end_date=None): | |
q = jsm.Quotes() | |
if start_date is None or end_date is None: | |
jsm_data = q.get_historical_prices(stockcode) | |
else: | |
jsm_data = q.get_historical_prices(stockcode, jsm.DAILY, start_date, end_date, jsm.DAILY) |
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