July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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174
5
章
pandas
入門
50% 1.400000 -2.900000
75% 4.250000 -2.100000
max 7.100000 -1.300000
数値データではない場合は、
describe
メソッドは別の要約統計量を提供します。
In [238]: obj = pd.Series(['a', 'a', 'b', 'c'] * 4)
In [239]: obj.describe()
Out[239]:
count 16
unique 3
top a
freq 8
dtype: object
要約統計量やそれに関連するメソッドの完全な一覧は、表5-8を確認してください。
表5-8 要約統計量の一覧
メソッド 説明
count
NA
ではない要素の数。
describe
シリーズやデータフレームの列に対して、複数の要約統計量を求める。
min
,
max
最小値、最大値を求める。
argmin
,
argmax
最小値、最大値が得られた要素のインデックス位置（整数）を求める。
idxmin
,
idxmax
最小値、最大値が得られた要素のラベルを求める。
quantile
データのパーセント点を
0
から
1
の範囲で求める。
sum
合計値。
mean
平均値。
median
中央値（
50
パーセント点）。
mad
平均値からの平均絶対偏差。
prod
すべての値の積。
var
標本分散。
std
標本標準偏差。
skew
標本歪度（
3
次のモーメント）。
kurt
標本尖度（
4
次のモーメント）。
cumsum
累積合計値。
cummin
,
cummax
累積の最小値と最大値 ...
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