In [1]:

    

from itertools import islice

import tables as tb
import numpy as np
import pandas as pd
from pandas import DataFrame, Series

import matplotlib.pyplot as plt

tbf = tb.open_file("/global/scratch/ryee/symbol_count/agg_count.h5", "a")
table = tbf.root.count_table


    

In [2]:

    

len(table)


    

    
Out[2]:





9953186

In [5]:

    

rows = table.iterrows()
rows


    

    
Out[5]:





Warning: Row iterator has not been initialized for table:
  /count_table (Table(9953186,)) ''
 You will normally want to use this object in iterator contexts.

In [6]:

    

[(row['symbol_root'], row['count']) for row in islice(rows,5)]


    

    
Out[6]:





[(b'OOK   ', 4939),
 (b'SUTR  ', 2652),
 (b'FSIN  ', 14228),
 (b'MPG   ', 36869),
 (b'CLWR  ', 55395)]

In [ ]:

    

# let's try reading the


    

In [7]:

    

tbf.close()


    

In [ ]:

    

# index
# index1 = table.cols.date.create_index()


    

In [ ]:

    

# read the first couple of rows (like df.head)


    

In [8]:

    

tbf = tb.open_file("/global/scratch/ryee/symbol_count/agg_count.h5", "a")
table = tbf.root.count_table.read()


    

In [12]:

    

table['count'].sum()


    

    
Out[12]:





851562577807

In [14]:

    

df = DataFrame(table)
df.head()


    

    
Out[14]:






  

    

      

      
symbol_root
      
count
      
date
    
  
  

    

      
0
      
b'OOK   '
      
4939
      
1271908800
    
    

      
1
      
b'SUTR  '
      
2652
      
1271908800
    
    

      
2
      
b'FSIN  '
      
14228
      
1271908800
    
    

      
3
      
b'MPG   '
      
36869
      
1271908800
    
    

      
4
      
b'CLWR  '
      
55395
      
1271908800
    
  

In [16]:

    

df["count"].sum()


    

    
Out[16]:





851562577807

In [25]:

    

cdf = DataFrame(df["date"].value_counts(), columns=['c'])
cdf['ts']= cdf.index
cdf.head()


    

    
Out[25]:






  

    

      

      
c
      
ts
    
  
  

    

      
1433995200
      
7582
      
1433995200
    
    

      
1434081600
      
7579
      
1434081600
    
    

      
1434340800
      
7579
      
1434340800
    
    

      
1433908800
      
7568
      
1433908800
    
    

      
1433476800
      
7564
      
1433476800
    
  

In [22]:

    

%matplotlib inline


    

In [26]:

    

cdf.plot(x='ts', y='c', kind='scatter')


    

    
Out[26]:





<matplotlib.axes._subplots.AxesSubplot at 0x2b50c87b3cf8>






    

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