Python error - name lengths

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By : GonGon

Date : November 27 2020, 01:01 AM

I wish did fix the issue. Here's the requirement: , why don't you check for bounds first?

code :

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Re-sampling groups of variable lengths so that group lengths are equal (R, dplyr)

By : Bunchi

Date : March 29 2020, 07:55 AM

wish helps you If I understood the question correctly, RESULT is some kind of a complement data frame to DATA such as when combined together they would produce 4 rows for each group.

code :

NUMBER <- 4

set.seed(1234)

RESULT2 <- DATA %>%
  group_by(SITE) %>%
  mutate(n = n(),
         sampsize = as.numeric( ifelse(n>=NUMBER,0,NUMBER-n)) ) %>%
  do( sample_n(., size=.$sampsize[1], replace=TRUE ) ) %>%
  select( -n, -sampsize ) %>%
  ungroup()

RESULT2

Source: local data frame [3 x 4]

  SITE STUFF STUFF2 STUFF3
1    B   100    200    400
2    C  6000  12000  24000
3    C  6000  12000  24000

NUMBER <- 4

set.seed(1234)

RESULT3 <- DATA %>%
  group_by(SITE) %>%
  mutate(n = n(),
         sampsize = as.numeric( ifelse(n>=NUMBER,0,NUMBER-n)) ) %>%
  do( rbind(.,sample_n(., size=.$sampsize[1], replace=TRUE )) ) %>%
  select( -n, -sampsize ) %>%
  ungroup()

RESULT3

Source: local data frame [12 x 4]

   SITE STUFF STUFF2 STUFF3
1     A     1      2      4
2     A     2      4      8
3     A    30     60    120
4     A    40     80    160
5     B   100    200    400
6     B   200    400    800
7     B   300    600   1200
8     B   100    200    400
9     C  5000  10000  20000
10    C  6000  12000  24000
11    C  6000  12000  24000
12    C  6000  12000  24000

python pandas: vectorized function value error "lengths do not match"

By : RebliNk17

Date : March 29 2020, 07:55 AM

Any of those help I believe you can use broadcasting:

code :

start_date_period = pd.period_range('2004-01-01', '12-31-2017', freq='30D')
end_date_period = pd.period_range('2004-01-30', '12-31-2017', freq='30D')

tra = df['transaction_dt'].values[:, None]
idx1 = np.argmax(tra < start_date_period.end_time.values, axis=1)
idx2 = np.argmin(tra > end_date_period.start_time.values, axis=1)

df['window_start_dt'] = start_date_period[idx1]
df['window_end_dt'] = end_date_period[idx2]
print (df)

   customer_id transaction_dt product  price  units window_start_dt  \
0            1     2004-01-02  thing1     25     47      2004-01-01   
1            1     2004-01-17  thing2    150      8      2004-01-01   
2            2     2004-01-29  thing2    150     25      2004-01-01   
3            3     2017-07-15  thing3     55     17      2017-06-21   
4            3     2016-05-12  thing3     55     47      2016-04-27   
5            4     2012-02-23  thing2    150     22      2012-02-18   
6            4     2009-10-10  thing1     25     12      2009-10-01   
7            4     2014-04-04  thing2    150      2      2014-03-09   
8            5     2008-07-09  thing2    150     43      2008-07-08   

  window_end_dt  
0    2004-01-30  
1    2004-01-30  
2    2004-01-30  
3    2017-07-20  
4    2016-05-26  
5    2012-03-18  
6    2009-10-30  
7    2014-04-07  
8    2008-08-06

error - lengths differ when trying to integrate (but lengths are the same)

By : Anwarsha Jamhar

Date : March 29 2020, 07:55 AM

this one helps. I believe this is a bug in the MESS package with the absolutearea flag set to TRUE.
If you look at the code for auc:

code :

if (absolutearea)
    myfunction <- function(x) { abs(splinefun(x, y, method="natural")) }
else
    myfunction <- splinefun(x, y, method="natural")

res <- integrate(myfunction, lower=from, upper=to)$value

How can I handle the error "Error: all(lengths == 1L | lengths == n) is not TRUE"?

By : Shubham

Date : March 29 2020, 07:55 AM

wish helps you gs_add_rows only can add rows once the header is available in the google sheet so you need to create the first row or the header information with gs_edit_cells() before you use add_rows.
This is explained in the googlesheets vignette.

Java. Find the lengths of strings in an array list for which those string lengths occur the most

By : user3574503

Date : March 29 2020, 07:55 AM

Hope this helps For example, say I have the following array after splitting it. , You can make use of Java Stream Library's groupingBy collector

code :

String[] arr = new String[]{
        "Hello",
        "world",
        "what",
        "a",
        "fine",
        "day",
        "it",
        "is",
        "the",
        "date",
        "is",
        "01/10/2020"
};

List<Integer> maxRepeatingSizes =
    Arrays.stream(arr)
            .collect(Collectors.groupingBy(
                String::length,
                Collectors.counting()
            )).entrySet()
            .stream()
            .collect(
                    Collectors.groupingBy(
                            Map.Entry::getValue,
                            Collectors.mapping(
                                Map.Entry::getKey,
                                Collectors.toList()
                            )
                    )
            ).entrySet()
            .stream()
            .max(
                    Map.Entry.comparingByKey()
            ).get()
            .getValue();