time_data = [
[2006, 11, 26, 2, 40],
[2009, 1, 16, 23, 35],
[2014, 5, 4, 14, 26],
[2017, 8, 9, 7, 5],
[2017, 4, 1, 22, 15]
]
resolt = time_data
print (resolt)
Numpy
lambda(ラムダ) filter (map,if)で条件に合うものを抽出
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1 2 3 4 5 6 7 8 9 10 |
例1 a = [1, -2, 3, -4, 5] list(filter(lambda x: x>0, aaa)) #xはこの場限りの変数aaaはフィルターしたい文字の入った変数 #変数aaaにある要素の数だけ繰り返す 例2 list(filter(lambda x: x > 1 and x < 7, tuki2)) |
DataFrame 縦、横に数値の差を求める
DataFrame型の変数に対して、変数.diff(変数.diff - x, axis="0 or 1")と指定で
行間または列間の差を計算したDataFrameが作成
第1引数が正の場合は前の行との差、負の場合は後の行との差
axisは0の場合が行(横)方向、1の場合が列(縦)方向です。
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1 |
<span role="presentation"><span class="cm-keyword">import</span> <span class="cm-variable">numpy</span> <span class="cm-keyword">as</span> <span class="cm-variable">np</span></span> |
|
1 |
<span role="presentation"><span class="cm-keyword">import</span> <span class="cm-variable">pandas</span> <span class="cm-keyword">as</span> <span class="cm-variable">pd</span></span> |
|
1 |
<span role="presentation"><span class="cm-variable">np</span>.<span class="cm-property">random</span>.<span class="cm-property">seed</span>(<span class="cm-number">0</span>)</span> |
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1 |
<span role="presentation"><span class="cm-variable">columns</span> = [<span class="cm-string">"apple"</span>, <span class="cm-string">"orange"</span>, <span class="cm-string">"banana"</span>, <span class="cm-string">"strawberry"</span>, <span class="cm-string">"kiwifruit"</span>]</span> |
|
1 |
<span role="presentation"></span> |
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1 |
<span role="presentation"><span class="cm-comment"># DataFrameを生成し、列を追加</span></span> |
|
1 |
<span role="presentation"><span class="cm-variable">df</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>()</span> |
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1 |
<span role="presentation"><span class="cm-keyword">for</span> <span class="cm-variable">column</span> <span class="cm-keyword">in</span> <span class="cm-variable">columns</span>:</span> |
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1 |
<span role="presentation"> <span class="cm-variable">df</span>[<span class="cm-variable">column</span>] = <span class="cm-variable">np</span>.<span class="cm-property">random</span>.<span class="cm-property">choice</span>(<span class="cm-builtin">range</span>(<span class="cm-number">1</span>, <span class="cm-number">11</span>), <span class="cm-number">10</span>)</span> |
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1 |
<span role="presentation"><span class="cm-variable">df</span>.<span class="cm-property">index</span> = <span class="cm-builtin">range</span>(<span class="cm-number">1</span>, <span class="cm-number">11</span>)</span> |
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1 |
<span role="presentation"></span> |
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1 |
<span role="presentation"><span class="cm-comment"># dfの各行について、2行後の行との差を計算したDataFrameをdf_diffに代入</span></span> |
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1 2 3 |
<span role="presentation"><span class="cm-variable">df_diff</span>=<span class="cm-variable">df</span>.<span class="cm-property">diff</span> <span class=" CodeMirror-matchingbracket">(</span><span class="cm-operator">-</span><span class="cm-number">2</span>,<span class="cm-variable">axis</span> = <span class="cm-number">0</span><span class=" CodeMirror-matchingbracket">) #第一引数がマイナスの場合は下、右方向へ処理 第一引数がプラスの場合は上、左方向へ処理</span></span> |
|
1 |
</code><code> |
|
1 |
<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df</span>)</span> |
|
1 |
<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df_diff</span>)</span> |
DataFrame 要約計量 平均、最大、最小、標準偏差等
列ごとの平均値、最大値、最小値等統計的情報を要約統計量と呼ぶ。
DataFrameの変数に対して、変数.describe()は変数の列ごとの
個数、平均値、標準偏差、最小値、四分位数、最大値を返す。
DataFrameのインデックスの数字は統計量の名前に置き換わる
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1 |
<span role="presentation"><span class="cm-keyword">import</span> <span class="cm-variable">numpy</span> <span class="cm-keyword">as</span> <span class="cm-variable">np</span></span> |
|
1 |
<span role="presentation"><span class="cm-keyword">import</span> <span class="cm-variable">pandas</span> <span class="cm-keyword">as</span> <span class="cm-variable">pd</span></span> |
|
1 |
<span role="presentation"><span class="cm-variable">np</span>.<span class="cm-property">random</span>.<span class="cm-property">seed</span>(<span class="cm-number">0</span>)</span> |
|
1 |
<span role="presentation"><span class="cm-variable">columns</span> = [<span class="cm-string">"apple"</span>, <span class="cm-string">"orange"</span>, <span class="cm-string">"banana"</span>, <span class="cm-string">"strawberry"</span>, <span class="cm-string">"kiwifruit"</span>]</span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-comment"># DataFrameを生成し、列を追加</span></span> |
|
1 |
<span role="presentation"><span class="cm-variable">df</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>()</span> |
|
1 |
<span role="presentation"><span class="cm-keyword">for</span> <span class="cm-variable">column</span> <span class="cm-keyword">in</span> <span class="cm-variable">columns</span>:</span> |
|
1 |
<span role="presentation"> <span class="cm-variable">df</span>[<span class="cm-variable">column</span>] = <span class="cm-variable">np</span>.<span class="cm-property">random</span>.<span class="cm-property">choice</span>(<span class="cm-builtin">range</span>(<span class="cm-number">1</span>, <span class="cm-number">11</span>), <span class="cm-number">10</span>)</span> |
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1 |
<span role="presentation"><span class="cm-variable">df</span>.<span class="cm-property">index</span> = <span class="cm-builtin">range</span>(<span class="cm-number">1</span>, <span class="cm-number">11</span>)</span> |
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1 |
<span role="presentation"><span class="cm-builtin">print</span><span class=" CodeMirror-matchingbracket">(</span><span class="cm-variable">df</span><span class=" CodeMirror-matchingbracket">)</span></span> |
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1 |
<span role="presentation"><span class="cm-comment"># dfの要約統計量のうち、"mean", "max", "min"を取り出してdf_desに代入してください</span></span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-variable">df_des</span> = <span class="cm-variable">df</span>.<span class="cm-property">describe</span>().<span class="cm-property">loc</span>[[<span class="cm-string">"mean"</span>, <span class="cm-string">"max"</span>, <span class="cm-string">"min"</span>]]</span> |
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1 |
<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df_des</span>)</span> |
DataFrame カラムの名称が異なるが意味が同じデータを繋げる
DataFrame 外部結合 合わないデータも結合
DataFrameの結合で共通するものが無くても結合し、
数値の孫座しない部分はNoneとなる
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1 2 3 |
<span role="presentation"><span class="cm-keyword"> import</span> <span class="cm-variable">numpy</span> <span class="cm-keyword">as</span> <span class="cm-variable">np</span></span> |
|
1 |
<span role="presentation"><span class="cm-keyword">import</span> <span class="cm-variable">pandas</span> <span class="cm-keyword">as</span> <span class="cm-variable">pd</span></span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-variable">data1</span> = {<span class="cm-string">"fruits"</span>: [<span class="cm-string">"apple"</span>, <span class="cm-string">"orange"</span>, <span class="cm-string">"banana"</span>, <span class="cm-string">"strawberry"</span>, <span class="cm-string">"kiwifruit"</span>],</span> |
|
1 |
<span role="presentation"> <span class="cm-string">"year"</span>: [<span class="cm-number">2001</span>, <span class="cm-number">2002</span>, <span class="cm-number">2001</span>, <span class="cm-number">2008</span>, <span class="cm-number">2006</span>],</span> |
|
1 |
<span role="presentation"> <span class="cm-string">"amount"</span>: [<span class="cm-number">1</span>, <span class="cm-number">4</span>, <span class="cm-number">5</span>, <span class="cm-number">6</span>, <span class="cm-number">3</span>]}</span> |
|
1 |
<span role="presentation"><span class="cm-variable">df1</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>(<span class="cm-variable">data1</span>)</span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-variable">data2</span> = {<span class="cm-string">"fruits"</span>: [<span class="cm-string">"apple"</span>, <span class="cm-string">"orange"</span>, <span class="cm-string">"banana"</span>, <span class="cm-string">"strawberry"</span>, <span class="cm-string">"mango"</span>],</span> |
|
1 |
<span role="presentation"> <span class="cm-string">"year"</span>: [<span class="cm-number">2001</span>, <span class="cm-number">2002</span>, <span class="cm-number">2001</span>, <span class="cm-number">2008</span>, <span class="cm-number">2007</span>],</span> |
|
1 |
<span role="presentation"> <span class="cm-string">"price"</span>: [<span class="cm-number">150</span>, <span class="cm-number">120</span>, <span class="cm-number">100</span>, <span class="cm-number">250</span>, <span class="cm-number">3000</span>]}</span> |
|
1 |
<span role="presentation"><span class="cm-variable">df2</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>(<span class="cm-variable">data2</span>)</span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-comment"># df1, df2の中身を確認してください</span></span> |
|
1 |
<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df1</span>)</span> |
|
1 |
<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df2</span>)</span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-comment"># df1とdf2を"fruits"をキーに外部結合して作成したDataFrameをdf3に代入してください</span></span> |
|
1 |
<span role="presentation"><span class="cm-variable">df3</span> = <span class="cm-variable">pd</span>.<span class="cm-property">merge</span>(<span class="cm-variable">df1</span>, <span class="cm-variable">df2</span>, <span class="cm-variable">on</span>=<span class="cm-string">"fruits"</span>, <span class="cm-variable">how</span>=<span class="cm-string">"outer"</span>)</span> |
|
1 |
<span role="presentation"></span> |
|
1 |
<span role="presentation"><span class="cm-builtin">print</span><span class=" CodeMirror-matchingbracket">(</span><span class="cm-variable">df3</span><span class=" CodeMirror-matchingbracket">)</span></span> |