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Pandas

DataFrame 列の追加とindexの追加 縦に増やす

2017年11月25日 by 河副 太智 Leave a Comment

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<span role="presentation"><span class="cm-keyword">DataFrame 列の追加とindexの追加 縦に増やす
 
import pandas as pd
​
index = ["a", "b", "c", "d", "e"]
data1 = [10, 5, 8, 12, 3]
data2 = [30, 25, 12, 10, 8]
series1 = pd.Series(data1, index=index)
series2 = pd.Series(data2, index=index)
​
new_column = pd.Series([15, 7], index=[0, 1])
#縦(カラム)に15と7を代入、indexで15を縦の0の位置に入れ、1を縦の1の位置に代入
​
# series1, seires2からDataFrameを生成
df = pd.DataFrame([series1, series2])
​
# dfの新しい列"f"にnew_columnのデータを追加
df["f"] = new_column
​
# 出力
print(df)</span></span>
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    a   b   c   d  e   f
0  10   5   8  12  3  15
1  30  25  12  10  8   7

Filed Under: Pandas

DataFrame 行の追加とindexの追加 横に増やす

2017年11月25日 by 河副 太智 Leave a Comment

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data = {"fruits": ["a", "b", "c", "d", "e"],
        "year": [2001, 2002, 2001, 2008, 2006],
        "time": [1, 4, 5, 6, 3]}
df = pd.DataFrame(data)
series = pd.Series(["f", 2008, 7], index=["fruits", "year", "time"])
#上記のindex=[...]が無いと余計な行が追加される、追加した要素が
どのindexに属するのかを指定する必要がある
 
df = df.append(series, ignore_index=True)

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出力結果

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       fruits  time  year
0       a     1  2001
1       b     4  2002
2       c     5  2001
3       d     6  2008
4       e     3  2006
5       f     7  2008

Filed Under: Pandas

DataFrame 行が(縦)index 列が(横)カラム

2017年11月25日 by 河副 太智 Leave a Comment

 

DataFrameの行の名前をインデックス(横) 指定した要素の名前、数だけ右に向かって出力
DataFrameの列の名前をカラム(縦)0~nまで要素の数だけ縦に自動で付記

 

 

DataFrameは、Seriesを複数束る2次元のデータ構造。
pandas.DataFrame()にSeriesを渡し、DataFrameを生成行には0から昇順に番号がつきます。

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<span class="cm-variable">pandas</span>.<span class="cm-property">DataFrame</span>([<span class="cm-variable">Series</span>, <span class="cm-variable">Series</span>, ...])
 

バリューにリストの辞書型を用いても作成可能
リスト型の長さは等しくする

コード

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<span class="cm-variable">data</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 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 class="cm-string">"time"</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 class="cm-variable">df</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>(<span class="cm-variable">data</span>)
<span class="cm-builtin">print</span>(<span class="cm-variable">df</span>)
 

出力結果

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fruits  time  year
0       apple     1  2001
1      orange     4  2002
2      banana     5  2001
3  strawberry     6  2008
4   kiwifruit     3  2006
 
 
 
 
例

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<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>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-variable">index</span> = [<span class="cm-string">"a"</span>, <span class="cm-string">"b"</span>, <span class="cm-string">"c"</span>, <span class="cm-string">"d"</span>, <span class="cm-string">"e"</span>]</span>

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<span role="presentation"><span class="cm-variable">data1</span> = [<span class="cm-number">10</span>, <span class="cm-number">5</span>, <span class="cm-number">8</span>, <span class="cm-number">12</span>, <span class="cm-number">3</span>]</span>

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<span role="presentation"><span class="cm-variable">data2</span> = [<span class="cm-number">30</span>, <span class="cm-number">25</span>, <span class="cm-number">12</span>, <span class="cm-number">10</span>, <span class="cm-number">8</span>]</span>

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<span role="presentation"><span class="cm-variable">series1</span> = <span class="cm-variable">pd</span>.<span class="cm-property">Series</span>(<span class="cm-variable">data1</span>, <span class="cm-variable">index</span>=<span class="cm-variable">index</span>)</span>

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<span role="presentation"><span class="cm-variable">series2</span> = <span class="cm-variable">pd</span>.<span class="cm-property">Series</span>(<span class="cm-variable">data2</span>, <span class="cm-variable">index</span>=<span class="cm-variable">index</span>)</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-comment"># series1, seires2からDataFrameを生成してdfに代入</span></span>

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<span role="presentation"><span class="cm-variable">df</span> = <span class="cm-variable">pd</span>.<span class="cm-property">DataFrame</span>([<span class="cm-variable">series1</span>,<span class="cm-variable">series2</span>])</span>

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<span role="presentation"><span class="cm-comment"># 出力</span></span>

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<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">df</span>)</span>
 
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      a        b       c          d           e
0     10       5       8          12          3
1     30      25      12          10          8

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Filed Under: Pandas

Serius でソート

2017年11月25日 by 河副 太智 Leave a Comment

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<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>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-variable">index</span> =  <span class=" CodeMirror-matchingbracket">[</span><span class="cm-string">"a"</span>, <span class="cm-string">"b"</span>, <span class="cm-string">"c"</span>, <span class="cm-string">"d"</span>, <span class="cm-string">"e"</span><span class=" CodeMirror-matchingbracket">]</span></span>

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<span role="presentation"><span class="cm-variable">data</span> = [<span class="cm-number">10</span>, <span class="cm-number">5</span>, <span class="cm-number">8</span>, <span class="cm-number">12</span>, <span class="cm-number">3</span>]</span>

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<span role="presentation"><span class="cm-variable">series</span> = <span class="cm-variable">pd</span>.<span class="cm-property">Series</span>(<span class="cm-variable">data</span>, <span class="cm-variable">index</span>=<span class="cm-variable">index</span>)</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-comment"># seriesをインデックスについてアルファベット順にソートしたSeriesをitems1に代入にしてください。</span></span>

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<span role="presentation"><span class="cm-variable">items1</span> = <span class="cm-variable">series</span>.<span class="cm-property">sort_index</span>()</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-comment"># seriesをデータについて値の大きさを昇順にソートしたSeriesをitems2に代入してください。</span></span>

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<span role="presentation"><span class="cm-variable">items2</span> = <span class="cm-variable">series</span>.<span class="cm-property">sort_values</span>()</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">items1</span>)</span>

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<span role="presentation"><span class="cm-builtin">print</span>()</span>

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<span role="presentation"><span class="cm-builtin">print</span>(<span class="cm-variable">items2</span>)</span>
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a    10
b     5
c     8
d    12
e     3
dtype: int64
 
e     3
b     5
c     8
a    10
d    12
dtype: int64

Filed Under: Pandas

Series 値の数値以上、以下 指定範囲で取り出し

2017年11月25日 by 河副 太智 Leave a Comment

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<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>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-variable">index</span> = [<span class="cm-string">"a"</span>, <span class="cm-string">"b"</span>, <span class="cm-string">"c"</span>, <span class="cm-string">"d"</span>, <span class="cm-string">"e"</span>]</span>

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<span role="presentation"><span class="cm-variable">data</span> = [<span class="cm-number">10</span>, <span class="cm-number">5</span>, <span class="cm-number">8</span>, <span class="cm-number">12</span>, <span class="cm-number">3</span>]</span>

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<span role="presentation"><span class="cm-variable">series</span> = <span class="cm-variable">pd</span>.<span class="cm-property">Series</span>(<span class="cm-variable">data</span>, <span class="cm-variable">index</span>=<span class="cm-variable">index</span>)</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-comment"># series内の要素のうち、値が5以上10未満の要素を含むSeriesを作り、seriesに再代入</span></span>

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<span role="presentation"><span class="cm-variable">series</span> = <span class="cm-variable">series</span>[<span class="cm-variable">series</span> <span class="cm-operator">&gt;</span>= <span class="cm-number">5</span>][<span class="cm-variable">series</span> <span class="cm-operator">&lt;</span> <span class="cm-number">10</span>]</span>

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<span role="presentation">​</span>

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<span role="presentation"><span class="cm-builtin">print</span><span class=" CodeMirror-matchingbracket">(</span><span class="cm-variable">series</span><span class=" CodeMirror-matchingbracket">)</span></span>
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b    5
c    8
dtype: int64

Filed Under: Pandas

series要素の削除

2017年11月25日 by 河副 太智 Leave a Comment

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import pandas as pd
​
index = ["a", "b", "c", "d", "e"]
data = [10, 5, 8, 12, 3]
​
# indexとdataを含むSeriesを作成しseriesに代入
series = pd.Series(data, index=index)
​
# インデックスがstrawberryの要素を削除してseriesに代入
series = series.drop("c")
​
print(series)
 
 結果
 
a    10
b     5
d    12
e     3
dtype: int64

 

Filed Under: Pandas

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