标签: crosstab

背景

我每月都有时间序列数据,我想对每个ID进行求和,按月分组,然后将月份名称作为列而不是行.

例

+----+------------+-------+-------+
| id | extra_info | month | value |
+----+------------+-------+-------+
| 1  | abc        | jan   | 10    |
| 1  | abc        | feb   | 20    |
| 2  | def        | jan   | 10    |
| 2  | def        | feb   | 5     |
| 1  | abc        | jan   | 15    |
| 3  | ghi        | mar   | 15    |

期望的结果

+----+------------+-----+-----+-----+
| id | extra_info | jan | feb | mar …

我是 PostgreSQL 的新手，正在使用 9.4 版。我有一个表，其中收集的测量值作为字符串，需要使用始终是最新的内容（例如 VIEW）将其转换为一种 PIVOT 表。
此外，一些值需要转换，例如乘以 1000，如下面的“sensor3”示例所示。

源表：

CREATE TABLE source (
    id bigint NOT NULL,
    name character varying(255),
    "timestamp" timestamp without time zone,
    value character varying(32672),
    CONSTRAINT source_pkey PRIMARY KEY (id)
);

INSERT INTO source VALUES
  (15,'sensor2','2015-01-03 22:02:05.872','88.4')
, (16,'foo27'  ,'2015-01-03 22:02:10.887','-3.755')
, (17,'sensor1','2015-01-03 22:02:10.887','1.1704')
, (18,'foo27'  ,'2015-01-03 22:02:50.825','-1.4')
, (19,'bar_18' ,'2015-01-03 22:02:50.833','545.43')
, (20,'foo27'  ,'2015-01-03 22:02:50.935','-2.87')
, (21,'sensor3','2015-01-03 22:02:51.044','6.56');

源表结果：

| id | name      | timestamp                 | value    |
|----+-----------+---------------------------+----------|
| 15 | …

我正在使用numpy 0.10.1和pandas 0.17.0的Python 3.4.1。我有一个大型的数据框，其中列出了单个动物的种类和性别。这是一个真实的数据集，不可避免地存在NaN表示的缺失值。数据的简化版本可以生成为：

import numpy as np
import pandas as pd
tempDF = pd.DataFrame({ 'id': [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],
                        'species': ["dog","dog",np.nan,"dog","dog","cat","cat","cat","dog","cat","cat","dog","dog","dog","dog",np.nan,"cat","cat","dog","dog"],
                        'gender': ["male","female","female","male","male","female","female",np.nan,"male","male","female","male","female","female","male","female","male","female",np.nan,"male"]})

打印数据框将得到：

    gender  id species
0     male   1     dog
1   female   2     dog
2   female   3     NaN
3     male   4     dog
4     male   5     dog
5   female   6     cat
6   female   7     cat
7      NaN   8     cat
8     male   9     dog
9     male  10     cat
10  female  11     cat
11    male  12     dog
12  female  13     dog
13  female  14 …

我有一个看起来像这样的数据集：

我想将所有co值汇总在一行中，因此最终结果如下所示：

看起来很容易，对吧？只需crosstab按照本答案中的建议使用 编写查询。问题是这要求我CREATE EXTENSION tablefunc;和我没有对我的数据库的写访问权限。

谁能推荐一个替代方案？

我想制作一个变量与 data.frame 中所有其他变量的交叉表。

library(tidyverse)
library(janitor)

humans <- starwars %>%
  filter(species == "Human")

humans %>%
  janitor::tabyl(gender, eye_color)



gender blue blue-gray brown dark hazel yellow
 female    3         0     5    0     1      0
   male    9         1    12    1     1      2

humans %>%
  dplyr::select_if(is.character) %>%
  dplyr::select(-name, -gender) %>%
  purrr::map(.f = ~janitor::tabyl(dat = humans, gender, .x))

Error: Unknown columns `blond`, `none`, `brown`, `brown, grey`, `brown` and ... 
Call `rlang::last_error()` to see a backtrace

我很难为PDF 编织的 R Markdown文档创建一个简单漂亮的交叉表。我有一个类似于这个例子的数据集：

library(tidyverse)
fakeData <- tibble(id = c(1,2,3,4,5,6,7,8,9,10),
                   bmi = c("normal", "overweighted", "underweighted", "normal", "normal", "overweighted",
                           "normal", "overweighted", "underweighted","normal"),
                   gender = c("M", "F", "M", "M", "F", "F", "M", "F", "F", "F"))

我想得到这样的输出：

有没有人有一个技巧/一个已知的好包来做到这一点？非常感谢！

statement我在 Postgres 中有下表：

stock |  year | statement    | amount           

ACME  | 2003  | Q1 Earnings  | 100
ACME  | 2003  | Q2 Earnings  | 200
ACME  | 2004  | Q2 Earnings  | 300 

如何制作一个新表，将一年的 4 个季度全部排在一行？以及缺失语句的空值。

stock | year | Q1 Earnings | Q2 Earnings | Q3 Earnings | Q4 Earnings 

ACME  | 2003 | 100         | 200         | Null        | Null
ACME  | 2004 | NULL        | 300         | Null        | Null

找到了这个答案：Postgres - Transpose Rows …

我有两个因素,我正在制作它的交叉表.

x<-table(clean$VMail.Plan,clean$International.Plan)

我实际上想以图形方式表示它:

mosaicplot(x,data=clean,color=2:4,legend=TRUE,las = 1)

正常的镶嵌图不是很吸引人,我无法使用ggplot2包使这更具吸引力.要么像热图还是泡泡？

实际的列联表:

        No   Yes
  No    27  239
  Yes  243 2159

我正在尝试计算表上的交叉表(恰好是一个简单的物化视图,但这应该无关紧要):

user=# select * from data;
 region |    date    | sum
--------+------------+-----
 East   | 2010-06-30 |  22
 East   | 2010-01-31 |  32
 East   | 2010-02-25 |  12
 North  | 2010-01-31 |  34
 North  | 2010-02-25 |  88
 South  | 2010-01-31 |  52
 South  | 2010-02-25 |  54
 South  | 2010-06-30 |  11
 West   | 2010-06-30 |  15
 West   | 2010-02-25 |  37
 West   | 2010-01-31 |  11
(11 rows)

当我尝试使用以下表达式计算数据交叉表时,出现错误:

user=# SELECT * FROM
       crosstab('select region, date, sum from x …

我们假设我们有这样的数据帧:

df = pd.DataFrame({'key' : ['one', 'two', 'three', 'four'] * 3,
                   'col' : ['A', 'B', 'C'] * 4,
                   'val1' : np.random.randn(12),
                   'val2' : np.random.randn(12),
                   'val3' : np.random.randn(12)})

key + col 是唯一的关键

我想让col值成为拆分列或交叉列表,最后看起来像这样:

第一个天真的方法pd.crosstab(df.key,df.col)在这里不起作用:

此代码pd.crosstab(df.key,df.col,values = df[['val1', 'val2', 'val3']], aggfunc = np.max)无法运行ValueError: Wrong number of items passed 3, placement implies 1

怎么运作？