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Check if multiple pd.DataFrames are equal


By : jaskru
Date : July 31 2020, 10:00 PM
Does that help Is there a Pythonic way (no loops or recursion) to check if more than two pd.DataFrames (e.g., a list of pd.DataFrames) are equal to each other? , Something like:
code :
all(x.equals(dfs[0]) for x in dfs)


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Split pandas dataframe into multiple dataframes with equal numbers of rows


By : Lukas Lukas
Date : March 29 2020, 07:55 AM
it fixes the issue There are many ways to do what you want, your method looks over-complicated. A groupby using a scaled index as the grouping key would work:
code :
df = pd.DataFrame(data=np.random.rand(100, 3), columns=list('ABC'))
groups = df.groupby(np.arange(len(df.index))/10)
for (frameno, frame) in groups:
    frame.to_csv("%s.csv" % frameno)

check if multiple value are equal or not equal using php


By : Esoj
Date : March 29 2020, 07:55 AM
around this issue How can i check if 5 variables are the same or not the same in a simple way? , You can check through array_unique() with count():-
code :
if(count(array_unique($checkcommon)) ==1){
   echo "All values are same";
}

Multiple condition check and filter between multiple dataframes


By : user1401784
Date : March 29 2020, 07:55 AM
Any of those help I have two dataframes and am trying to use one dataframe as the filtering df and the other is the one being filtered. Here is how the two dataframes look like: , Use:
code :
#create dict for map if one word phrase
d = df.set_index('phrase1')['date1'].to_dict()

#if splitted strings like in original df
#d = {c: b for a, b in zip(df['phrase1'], df['date1']) for c in a.split()}
#print (d)

#join togther for list of tuples
zipped = zip(df1['phrase2'], df1['date2'])
#max Timestamp contant
mt = pd.Timestamp.max
#nested list comprehension with filtering
a = [' '.join([y for y in a.split() if not (d.get(y, mt) < b and y in d)]) for a, b in zipped]
print (a)
['cat nip', 'baobab tree', 'lazy', 'poor', 'fat cat']

df1['phrase2'] = a
print (df1)
      id      phrase2      date2
0  abc12      cat nip 2003-03-04
1  def34  baobab tree 2009-05-02
2  ghi56         lazy 2011-08-27
3  jkl78         poor 2014-08-27
4  mno90      fat cat 2008-08-27

Create multiple dataframes by filtering subsets that are not equal to a value in R


By : user2771660
Date : March 29 2020, 07:55 AM
To fix this issue Here's a way using lapply. This creates a list of your desired dataframes.
code :
colours <- c("blue", "white", "green", "yellow")

result <- lapply(colours, function(x) {
             df %>% filter(!Colours == x)
          }) %>% 
          setNames(paste0("NOT_", colours))

result

$NOT_blue
   Text Colours
1 text2   white
2 text3   green
3 text4  yellow

$NOT_white
   Text Colours
1 text1    blue
2 text3   green
3 text4  yellow

$NOT_green
   Text Colours
1 text1    blue
2 text2   white
3 text4  yellow

$NOT_yellow
   Text Colours
1 text1    blue
2 text2   white
3 text3   green

Merging DataFrames on multiple conditions - not specifically on equal values


By : Yang Lidar
Date : March 29 2020, 07:55 AM
To fix this issue I've just thought of a way to solve this - by combining my two methods:
First, focus on the individual chromosomes, and then loop through the genes in these smaller dataframes. This also doesn't have to make use of any SQL queries either. I've also included a section to immediately identify any redundant genes that don't have any SNPs that fall within their range. This makes use of a double for-loop which I normally try to avoid - but in this case it works quite well.
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