describe()方法用于计算一些统计数据,例如Series或DataFrame的数值的百分位数,均值和 std 。它分析数字和对象Series以及混合数据类型的DataFrame列集。
DataFrame.describe(percentiles=None, include=None, exclude=None)
它返回Series和DataFrame的统计摘要。
import pandas as pd import numpy as np a1 = pd.Series([1, 2, 3]) a1.describe()
输出
count 3.0 mean 2.0 std 1.0 min 1.0 25% 1.5 50% 2.0 75% 2.5 max 3.0 dtype: float64
import pandas as pd import numpy as np a1 = pd.Series(['p', 'q', 'q', 'r']) a1.describe()
输出
count 4 unique 3 top q freq 2 dtype: object
import pandas as pd import numpy as np a1 = pd.Series([1, 2, 3]) a1.describe() a1 = pd.Series(['p', 'q', 'q', 'r']) a1.describe() info = pd.DataFrame({'categorical': pd.Categorical(['s','t','u']), 'numeric': [1, 2, 3], 'object': ['p', 'q', 'r'] }) info.describe(include=[np.number]) info.describe(include=[np.object]) info.describe(include=['category'])
输出
categorical count 3 unique 3 top u freq 1
import pandas as pd import numpy as np a1 = pd.Series([1, 2, 3]) a1.describe() a1 = pd.Series(['p', 'q', 'q', 'r']) a1.describe() info = pd.DataFrame({'categorical': pd.Categorical(['s','t','u']), 'numeric': [1, 2, 3], 'object': ['p', 'q', 'r'] }) info.describe() info.describe(include='all') info.numeric.describe() info.describe(include=[np.number]) info.describe(include=[np.object]) info.describe(include=['category']) info.describe(exclude=[np.number]) info.describe(exclude=[np.object])
输出
categorical numeric count 3 3.0 unique 3 NaN top u NaN freq 1 NaN mean NaN 2.0 std NaN 1.0 min NaN 1.0 25% NaN 1.5 50% NaN 2.0 75% NaN 2.5 max NaN 3.0
祝学习愉快!(内容编辑有误?请选中要编辑内容 -> 右键 -> 修改 -> 提交!)