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How to find the number of rows in data frame that are almost duplicates i.e. differ by less than two entries?


By : khanos
Date : October 14 2020, 02:21 PM
This might help you How about this code. A quick solution by a beginner here, but I think it works OK.
code :
import pandas as pd
# let's create the dataframe
df = pd.DataFrame(data = {'col1': ['a','a','a','a'], 
                          'col2': ['b','a','b','q'],
                          'col3': ['c','c','c','q'],
                          'col4': ['d','d','d','q'], 
                          'col5': ['e','e','a','q'],
                          'col6': ['f','f','a','q'],
                          'col7': ['g','g','g','q']} )

almost_dups = []            # initialize the list we want to compute    
for i in range(len(df)):    # for every dataframe row
    a = df.iloc[i].values   # get row values
    count = 0               # this will count the rows similar to the selected one 
    for j in range(len(df)): # for every other row
        if i!=j:            # if rows are different
            b = df.iloc[j].values
            if sum([i == j for i, j in zip(a, b)])>= 5: # if at least 5 values are same
                count +=1   # increase counter
    almost_dups.append(count) # append the count
df['almost_dups'] = almost_dups   # append the list to dataframe, as a new column


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Python Pandas, how to find the number of entries in a sub-index in data frame


By : Arvind Srivastava
Date : March 29 2020, 07:55 AM
like below fixes the issue The only solution I know is to reset the index before performing a groupby. I have made a simple reproductible example below, it has to be adapted to your use case.
It should work but there is maybe a better solution. I will have a look.
code :
# Creating test data
np.random.seed(0)
df = pd.DataFrame(np.random.randint(0,10,size=(10, 4)), 
                  columns=list('ABCD'))
df = df.set_index(['A', 'B'])

# Reset the index,
# group by the first level and count the number of second level
# nunique can also be used to get the number of unique values

df.reset_index(level=1).groupby(level=0)['B'].count()

# A
# 2    1
# 3    1
# 4    1
# 5    3
# 7    2
# 8    2
df.reset_index(level=1).index.value_counts()

# 5    3
# 8    2
# 7    2
# 4    1
# 3    1
# 2    1

add duplicates to some rows and change order of rows in a data frame


By : user299119
Date : March 29 2020, 07:55 AM
I hope this helps . I would like to duplicate some rows in a data frame. , df2 is the final output.
code :
library(tidyverse)

df2 <- df %>%
  mutate(index = ifelse(index %in% "N-S", list(rep("N-S", 2)),
                        ifelse(index %in% "OS", list(rep("OS", 3)), list("E-W")))) %>%
  unnest() %>%
  group_by(yrmonth) %>%
  mutate(ID = c(1, 3, 5, 2, 4, 6)) %>%
  arrange(yrmonth, ID) %>%
  select(yrmonth, index, N, data)

Find relevant entries in existing data.frame and store these items in a new data.frame


By : Ahmad Jayyusi
Date : March 29 2020, 07:55 AM
I hope this helps you . I got a data.frame and want to calculate correlations of user and the ratings of different sport events. In a programming language like Java I would probably use two for loops to create my new data frame or collection. I guess in R there is a more comfortable way to achieve this? , Using tidyverse
code :
install.packages("tidyverse")
library(tidyverse)
df1 <- df %>%
          arrange(User, Event)
df2 <- split(df1, df1$User)
df3 <- map_df(df2, ~.x$RatingValue)
C <- cor(df3)

Transpose rows and columns in data frame using first column entries as colnames in new R data frame


By : aghoribabaji
Date : March 29 2020, 07:55 AM
this will help My data frame df looks like this: , Hope this helps!
code :
library(tibble)
library(dplyr)

df %>%
  t() %>%
  as.data.frame(stringsAsFactors = F) %>%
  rownames_to_column("value") %>%
  `colnames<-`(.[1,]) %>%
  .[-1,] %>%
  `rownames<-`(NULL)
  ID name1 name2 name50
1  A     4     5      4
2  B     6     8      6
3  C     7     3      7
4  D     8     5      8
df <- structure(list(ID = c("name1", "name2", "name50"), A = c(4L, 
5L, 4L), B = c(6L, 8L, 6L), C = c(7L, 3L, 7L), D = c(8L, 5L, 
8L)), .Names = c("ID", "A", "B", "C", "D"), class = "data.frame", row.names = c(NA, 
-3L))

How to find detect duplicates of single values in all rows and columns in R data.frame


By : user3503104
Date : March 29 2020, 07:55 AM
should help you out I have a large data-set consisting of a header and a series of values in that column. I want to detect the presence and number of duplicates of these values within the whole dataset. , You can use table() and data.frame() to see the occurrence
code :
data.frame(table(v))
     v Freq
1    1    1
2    2    1
3    3    1
4    4    1
5    5    1
6    6    1
7    7    1
8  346    1
9  455    1
10 456    2
11 482    1
12 483    1
13 545    2
14 734    3
15 783    1
16 874    1
17 948    1
v <- c(1, 2, 3, 4, 5, 6, 7, 734, 456, 346, 545, 874, 734, 455, 734, 
783, 482, 545, 456, 948, 483)
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