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how to filter rows based on


how to filter rows based on

By : ziggy
Date : November 21 2020, 03:00 PM
I hope this helps . I have a dataframe in pandas where one of the column (i.e., column 'b') contains strings with $ symbols:
code :
In [64]: df = pd.DataFrame({'a': [51, 2,32,99,81], 'b': ['$3', '$4','$-','$0','$23']})

In [65]: df['b'] = pd.to_numeric(df['b'].str.replace(r'\D+', ''), errors='coerce')

In [67]: df
Out[67]:
    a     b
0  51   3.0
1   2   4.0
2  32   NaN
3  99   0.0
4  81  23.0

In [68]: df = df[df['b'].notnull() & df['b'].ne(0)]

In [69]: df
Out[69]:
    a     b
0  51   3.0
1   2   4.0
4  81  23.0
In [73]: df = df.query("b == b and b != 0")

In [74]: df
Out[74]:
    a     b
0  51   3.0
1   2   4.0
4  81  23.0


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Linq to Entities : How to filter master table rows based on child rows properties

Linq to Entities : How to filter master table rows based on child rows properties


By : Dice Artist
Date : March 29 2020, 07:55 AM
wish of those help I have a master table Person and a detail table Events , This works!
code :
var q = from p in db.Persons
        join ev in db.Events on p.Id equals ev.PersonId
        where ev.SomeId == 4
        select p;
How to filter duplicate rows and filter rows based on a single column value?

How to filter duplicate rows and filter rows based on a single column value?


By : elsvf
Date : March 29 2020, 07:55 AM
I hope this helps you . , You can do this to avoid using DISTINCT.
code :
SELECT  co.id
FROM    customer_order co
WHERE   status = 'h'
        AND order_date BETWEEN '1/1/2016' AND '12/31/2016'
        AND NOT EXISTS ( SELECT 1
                         FROM   user_def_fields udf
                         WHERE  udf.document_id = co.id
                                AND string_val IN ('questions','credit card','credit hold','design')  
        )
SELECT  co.id
FROM    customer_order co
        LEFT JOIN user_def_fields udf ON udf.document_id = co.id 
            AND udf.string_val IN ('questions','credit card','credit hold','design') 
WHERE   co.status = 'h'
        AND order_date BETWEEN '1/1/2016' AND '12/31/2016'
        AND udf.document_id IS NULL
Filter rows in PostgreSQL based on values of consecutive rows in one column

Filter rows in PostgreSQL based on values of consecutive rows in one column


By : Erwan ZAMORA MEDINA
Date : March 29 2020, 07:55 AM
To fix this issue So I'm working with the following postgresql table: , You can do this with lag():
code :
select distinct business_id
from (select t.*,
             lag(year) over (partition by business_id order by year, month) as prev_year,
             lag(month) over (partition by business_id order by year, month) as prev_month,
             lag(rating) over (partition by business_id order by year, month) as prev_rating
      from us_business_monthly_review_growth t
     ) t
where rating >= $threshhold and prev_rating >= $threshhold and
      (year * 12 + month) = (prev_year * 12 + prev_month) + 1;
How to filter rows based on comparison with values in other rows, in a grouped data frame in R?

How to filter rows based on comparison with values in other rows, in a grouped data frame in R?


By : Criss Zahid
Date : March 29 2020, 07:55 AM
will help you A solution using . First, I converted all your numbers to numeric.
code :
library(tidyverse)

df <- df %>% mutate_at(vars(-contig), funs(as.numeric(as.character(.))))
df2 <- df %>%
  group_by(contig) %>%
  summarise(Diff = ifelse(n() > 1, list(combn(pos, 2)), list(NA))) %>%
  mutate(Flag = map_lgl(Diff, function(x){
    if (is.null(dim(x))){
      return(TRUE)
    } else {
      return(all(abs(x[1, ] - x[2, ]) > 50))
    }
  })) %>%
  right_join(df, by = "contig") %>%
  filter(Flag | (m_p_prop < 0.05 & f_p_prop < 0.05) | (m_q_prop < 0.05 & f_q_prop < 0.05)) %>%
  select(-Diff, -Flag)

df2
# A tibble: 7 x 6
#   contig         pos m_p_prop f_p_prop m_q_prop f_q_prop
#   <fct>        <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
# 1 Contig101702 12048  0.979    0.505    0.0211     0.495
# 2 Contig101702 13281  0.979    0.500    0.0208     0.500
# 3 Contig103637  1398  0.984    0.509    0.0155     0.491
# 4 Contig117031  3236  0.971    0.481    0.0287     0.519
# 5 Contig118816  3700  0.979    0.509    0.0206     0.491
# 6 Contig120914 56298  0.0195   0.0491   0.980      0.951
# 7 Contig120914 56326  0.00480  0.00120  0.00520    0.999
Creating function to filter and calculate division of rows based on filter?

Creating function to filter and calculate division of rows based on filter?


By : Matthew
Date : March 29 2020, 07:55 AM
Does that help I have a df such as below: , You can use groupby and len():
code :
df.groupby(by='Status').apply(lambda x: len(x)/len(df))

Status
Cancelled    0.666667
Processed    0.333333
dtype: float64
cc = df.groupby(by='Color').ID.count()
df.groupby(by=['Color', 'Status']).apply(lambda x: len(x)/cc.loc[x.Color.iloc[0]])

Color  Status   
Blue   Cancelled    0.666667
       Processed    0.333333
Green  Cancelled    0.666667
       Processed    0.333333
Red    Processed    1.000000
dtype: float64
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