June 2024
Intermediate to advanced
200 pages
4h 46m
Japanese
Content preview from Python2年生 データ分析のしくみ 第2版 体験してわかる！会話でまなべる！
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47
表データを読み込もう
LESSON
04
data = {"列名":[列データ], "列名":[列データ], "列名":[列データ]}
idx = [
インデックス名のリスト]
データフレーム = pd.DataFrame(data, index=idx)
import pandas as pd
data = {
"
国語" : [60,80,100],
"
数学" : [65,85,100],
"
英語" : [66,88,100]
}
idx = ["A
太","B介","C子"]
df = pd.DataFrame(data, index=idx)
df
JupyterNotebook
で外部デ ータファイルを 準備する
このように、データをプログラム内に書くとすぐ試せるので便利ですが、データ量が多
くなってくると大変です。そこで、外部に用意されたデータファイル（
CSVファイル）を
読み込んでデータフレームを作る方法を見てみましょう。
Jupyter Notebookでは、読み込むデータファイルは、ノートブックファイルと同じフォル
ダに置いておきます。
Jupyter Notebookのフォルダがどこかよくわからない場合は、Jupyter
Notebook
のHome画面を使いましょう。アップロードするフォルダを開いて右上の❶
［
Upload］ボタンをクリックすると、ファイル選択のダイアログが表示されるので、❷使う
CSVファイルを選んで、❸［選択］ボタンをクリックすると、❹アップロードできます。
書式：列データから、データフレームを作る ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.