Generate matrix summary report in SQLplus

I have following coloumns in a table
PERSON      (id)
EDU     (educated,non-educated)
CITY     citycode
COUNTRY     countrycode
I have to generate matrix summary report in SQLplus.
I have to print countrycode in vertical coloumn(LEFT MOST),
I have to print citycode in horizontal row(TOP MOST),
I have to print count(educated),count(non-educated),total(educated+non educated) in each city
in matrix cells.
Every city code will have three coloumns below it (three counts).
I need help in this problem.
Thanks in advance.
Regards.

The following is one method. You will need to modify it and expand it for the appropriate city codes and number of cities or create it dynamically. You will need to substitute the actual city codes for CITY1, CITY2, CITY3, etc. You will also need to substitute your table name for your_table. This example assumes that the edu column is populated with N for non-educated or Y for educated; If not, then you will need to modify that, too. You could also use the CASE statement or write it in PL/SQL, or use the Reports module of Developer 2000, or various other alternatives. This is just one suggestion.
SELECT   country,
         SUM (DECODE (city, 'CITY1', educated))        AS city1_educated,
         SUM (DECODE (city, 'CITY1', non_educated))    AS city1_non_educated,
         SUM (DECODE (city, 'CITY1', total))           AS city1_total,
         SUM (DECODE (city, 'CITY2', educated))        AS city2_educated,
         SUM (DECODE (city, 'CITY2', non_educated))    AS city2_non_educated,
         SUM (DECODE (city, 'CITY2', total))           AS city2_total,
         SUM (DECODE (city, 'CITY3', educated))        AS city3_educated,
         SUM (DECODE (city, 'CITY3', non_educated))    AS city3_non_educated,
         SUM (DECODE (city, 'CITY3', total))           AS city3_total
FROM     (SELECT   country,
                   city,
                   SUM (DECODE (edu, 'Y', 1, 0)) AS educated,
                   SUM (DECODE (edu, 'N', 1, 0)) AS non_educated,
                   COUNT (*)                     AS total
          FROM     your_table
          GROUP BY country, city)
GROUP BY country

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    Regards.

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    *<PERIOD_NAME>OCT-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<PERIOD_NAME>NOV-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<G_PERIOD_NAME>*
    *<PERIOD_NAME>OCT-08</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
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    *<G_PERIOD_NAME>*
    *<PERIOD_NAME>OCT-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
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    *<PERIOD_NAME>SEP-08</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<PERIOD_NAME>SEP-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<G_ACCT>*
    *<ACCT>791010</ACCT>*
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    *<LIST_G_DEPR1>*
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    *<PERIOD_NAME>AUG-08</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<PERIOD_NAME>AUG-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
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    *<PERIOD_NAME>DEC-08</PERIOD_NAME>*
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    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *<G_PERIOD_NAME>*
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    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
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    *<G_PERIOD_NAME>*
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    *<LIST_G_DEPR1>*
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    *<G_PERIOD_NAME>*
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    *<LIST_G_DEPR1>*
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    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *<G_PERIOD_NAME>*
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    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *<G_PERIOD_NAME>*
    *<PERIOD_NAME>OCT-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *<G_PERIOD_NAME>*
    *<PERIOD_NAME>SEP-08</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *<G_PERIOD_NAME>*
    *<PERIOD_NAME>SEP-09</PERIOD_NAME>*
    *<LIST_G_DEPR1>*
    *</LIST_G_DEPR1>*
    *</G_PERIOD_NAME>*
    *</LIST_G_PERIOD_NAME>*
    *</G_ACCT>* <G_ACCT>
    <ACCT>791012</ACCT>
    <CATEGORY>LEASEHOLDS</CATEGORY>
    <LIST_G_PERIOD_NAME>
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    <PERIOD_NAME>APR-09</PERIOD_NAME>
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    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>4</PERIOD_INDEX>
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    <DEPR1>3796.07</DEPR1>
    <FISCAL_YEAR>2010</FISCAL_YEAR>
    <PERIOD_INDEX>4</PERIOD_INDEX>
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    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2008</FISCAL_YEAR>
    <PERIOD_INDEX>8</PERIOD_INDEX>
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    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>8</PERIOD_INDEX>
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    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2008</FISCAL_YEAR>
    <PERIOD_INDEX>12</PERIOD_INDEX>
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    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3796.07</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>12</PERIOD_INDEX>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>2</PERIOD_INDEX>
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    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3796.07</DEPR1>
    <FISCAL_YEAR>2010</FISCAL_YEAR>
    <PERIOD_INDEX>2</PERIOD_INDEX>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>1</PERIOD_INDEX>
    </G_DEPR1>
    </LIST_G_DEPR1>
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    <G_PERIOD_NAME>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3796.07</DEPR1>
    <FISCAL_YEAR>2010</FISCAL_YEAR>
    <PERIOD_INDEX>1</PERIOD_INDEX>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2008</FISCAL_YEAR>
    <PERIOD_INDEX>7</PERIOD_INDEX>
    </G_DEPR1>
    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>7</PERIOD_INDEX>
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    </LIST_G_DEPR1>
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    <LIST_G_DEPR1>
    <G_DEPR1>
    <DEPR1>3798.76</DEPR1>
    <FISCAL_YEAR>2009</FISCAL_YEAR>
    <PERIOD_INDEX>6</PERIOD_INDEX>
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    <LIST_G_DEPR1>
    <G_DEPR1>
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