Example 8-10 Performing Basic Correlation Calculations

This example first creates a temporary database table, with its corresponding proxy oml.DataFrame object oml_df1, from the pandas.DataFrame object df. It then verifies the correlation computed between columns A and B, which gives 1, as expected. The values in B are twice the values in A element-wise. The example also changes a value field in df and creates a NaN entry. It then creates a temporary database table, with the corresponding proxy oml.DataFrame object oml_df2. Finally, it invokes the corr method on oml_df2 with skipna set to True ( the default) and then False to compare the results.

import oml
import pandas as pd

df = pd.DataFrame({'A': range(4), 'B': [2*i for i in range(4)]})
oml_df1 = oml.push(df)

# Verify that the correlation between column A and B is 1.
oml_df1.corr()

# Change a value to test the change in the computed correlation result.
df.loc[2, 'A'] = 1.5

# Change an entry to NaN (not a number) to test the 'skipna'
# parameter in the corr method.
df.loc[1, 'B'] = None

# Push df to the database using the floating point column type 
# because NaNs cannot be used in Oracle numbers.
oml_df2 = oml.push(df, oranumber=False)

# By default, 'skipna' is True.
oml_df2.corr()
oml_df2.corr(skipna=False)

Listing for This Example

>>> import oml
>>> import pandas as pd
>>>
>>> df = pd.DataFrame({'A': range(4), 'B': [2*i for i in range(4)]})
>>> oml_df1 = oml.push(df)
>>>
>>> # Verify that the correlation between column A and B is 1.
... oml_df1.corr()
   A  B
A  1  1
B  1  1
>>>
>>> # Change a value to test the change in the computed correlation result.
... df.loc[2, 'A'] = 1.5
>>>
>>> # Change an entry to NaN (not a number) so to test the 'skipna'
... # parameter in the corr method.
... df.loc[1, 'B'] = None
>>>
>>> # Push df to the database using the floating point column type 
... # because NaNs cannot be used in Oracle numbers.
... oml_df2 = oml.push(df, oranumber=False)
>>>
>>> # By default, 'skipna' is True.
... oml_df2.corr()
          A         B
A  1.000000  0.981981
B  0.981981  1.000000
>>> oml_df2.corr(skipna=False)
     A    B
A  1.0  NaN
B  NaN  1.0