(1)‘split’ : dict like {index -> [index], columns -> [columns], data -> [values]} split 将索引总结到索引,列名到列名,数据到数据。将三部分都分开了 (2)‘records’ : list like [{column -> value}, … , {column -> value}] records 以columns:values的形式输出 (3)‘index’ : dic...
5.2 多列分组 Multiple columns 6.1 特征 Features 6.1 定量特征 Quantitative 6.2 加权特征 Weigthed features 7.1 过滤条件 Filter conditions 7.2 用函数过滤 Filters from functions 7.3 特征过滤 Feature filtering 8.1 特征排序 Sorting by features 9.1 数值指标 Numeric metrics 9.2 分类特征 Categorical features 10...
describe is one such example, producing multiple summary statistic in one shot: --> (describe()方法是对列变量做描述性统计)"describe() 返回列变量分位数, 均值, count, std等常用统计指标" " roud(2)保留2位小数" df.describe().round(2) ...
2.columns 列索引 3.T 转置 4.values 值索引 5.describe 快速统计 行索引: 列索引: T转置: values 值索引: describe 快速统计 ---恢复内容开始--- series数据操作: 增: 删: 改: 查: 算术运算符: """add 加(add) sub 减(substract) div 除(divide) mul 乘(multiple)""" 加: 减: 乘: 除: 当...
():显示 DataFrame 的简要摘要,包括索引类型、列名、非空值计数和数据类型; dtypes:查看数据的数据类型; describe():生成DataFrame的描述性统计信息,包括均值、标准差、最小值、最大值及25%、50%、75%分位数; shape:返回数据的形状(行数,列数); index:返回DataFrame行索引; columns:返回DataFrame的列名; value...
# 查看特定选项print("\n'display.max_rows'选项:")print(pd.describe_option('display.max_rows')) 1. 2. 3. 7. 上下文管理器临时设置 7.1 临时修改设置 # 使用option_context临时修改设置withpd.option_context('display.max_rows',10,'display.max_columns',5):print("\n临时设置下的显示:")print(...
describe is one such example, producing multiple summary statistic in one shot: --> (describe()方法是对列变量做描述性统计) "describe() 返回列变量分位数, 均值, count, std等常用统计指标"" roud(2)保留2位小数"df.describe().round(2) 1. 2. 3. 4. 'describe() 返回列变量分位数, 均值,...
['父母子女个数'])#任务5:学会使用pandas describe()函数查看数据基本统计信息frame2 = pd.DataFrame([[1.4, np.nan], [7.1, -4.5], [np.nan, np.nan], [0.75, -1.3] ], index=['a', 'b', 'c', 'd'], columns=['one', 'two'])frame2#使用describe()函数查看基本信息frame2.describe()...
pandas.series.describe syntax You can also use the Pandas describe method on pandas Series objects instead of dataframes. The most common use of this though is to usedescribe()on individual columns of a Pandas dataframe (remember, each column of a dataframe is technically a Pandas Series). ...
'describe','diff','dtypes','expanding','ffill','fillna','filter','first','get_group','groups','head','hist','idxmax','idxmin','indices','last','mad','max','mean','median','min','ndim','ngroup','ngroups','nth','nunique','ohlc','pad','pct_change','plot','prod','...