Multi-dataframe For Loop Analysis Python -


i have data looks following:

data#1 class1: name1 name2 name3 name4  class2: name5 name6 name7  class3: name8 name9 name10 name11 name12 name13 … class500: namex namey

where above has 500 classes school given names corresponding class

next, have data set has of names (some not included in classes) looks following (pairwise correlation coefficients):

data#2            name1    name2     name3 …………………………………….. name4000 name1:     1        .96         .5 name2:    0.5         1         -.6 name3:  0.40        -.45          1 ………………………………………………………………………………………………. name4000: -.24        .08          .9    ………………………………………..     1

my goal take data dataframe1 , analyze each classes genes data 2. meaning; might this:

class1df: 

        name1       name2      name3      name4 name1     1          .5        .96         .5 name2     0.5        1         -.6         .8 name3     0.4       -.45        1        0.03 name4      .7          .76       .4           1

and build dataframe every single class.

after getting of these new data frames, wish calculate mean , other statistical calculations each new dataframe generate.

    class1 class2 class3 ... etc... etc... max min mean

i have written can insert, “class 50”, , i’ll want. however, don't want have 500 classes. therefore question is,

how do “smart” way? i’m trying write loops same thing on , on again...but don’t know begin writing/or how write them :(

i suppose should noted calculations @ end want able see (perhaps big data frame table?)

any or guidance appreciated! sample of have written below showcase have done before:

‘’’ finding class want @ (the problem want answer, how do of classes) ‘’’ <load data#1> classname = “class1” classnamecall = data#1.loc[classname] classnamecall = classnamecall.dropna() classnamecall = classnamecall.upper()  ‘’’ next data table ‘’’ <load data#2> myclass = data#2.loc[classnamecall,classnamecall] myclass = myclass.dropna(axis=0, how=’all’) myclass = myclass.dropna(axis=1,how=’all’) ntot = myclass.groupby(myclass.index).size() tot = ntot.sum()   ‘’’ data analysis ‘’’ calculate min/max/mean myclass…

i can find , analyze specific class if choose, again, want able every class. what’s best way go this?

i sorry wall of text, , thank each of in advance reading , helping! let me know if you'd me provide more information, or if question unclear! again!


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