notebook.community

Edit and run



In [1]:

    
%matplotlib inline



In [2]:

    
from os import path,listdir



In [3]:

    
import re



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import pandas as pd



In [5]:

    
case="./ras"



In [6]:

    
tablesDir=path.join(case,"tables")



In [7]:

    
rawTables={}
tableFileRExp=re.compile("Table_([0-9]+).csv")
for f in listdir(tablesDir):
    m=tableFileRExp.match(f)
    if m:
        val=int(m.group(1))
        rawTables[val]=pd.read_csv(path.join(tablesDir,f))

Check number of variables in the files



In [8]:

    
pd.Series(dict((k,len(rawTables[k].keys())) for k in rawTables))









    Out[8]:





0       55
10      59
30      55
100     55
150     55
200     55
250     55
300    108
325     55
350     55
375     55
400     55
420     55
430     55
432     55
433     55
dtype: int64

Plot first and second $H_2$



In [9]:

    
rawTables[300][["H2","H2.1"]].plot()









    Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x110d8a198>

For comparison: $H_2$ from another Table



In [11]:

    
rawTables[350][["H2"]].plot()









    Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x110d19278>

Get names of the duplicates



In [12]:

    
tooMuch=[k for k in range(len(rawTables[300].keys())) if rawTables[300].keys()[k][-2:]==".1"]



In [13]:

    
wrong=[k for k in rawTables[300].keys() if k[-2:]==".1"]



In [14]:

    
cleaned=rawTables[300].drop(wrong,axis=1)



In [15]:

    
cleaned.to_csv("Table_300_cleaned.csv",index=False)

Another table with extra values



In [16]:

    
set(rawTables[10].keys())-set(rawTables[0].keys())









    Out[16]:





{'coord', 'node', 'u+', 'v'}



In [17]:

    
set(rawTables[0].keys())-set(rawTables[10].keys())









    Out[17]:





set()



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