20121113 (ON)
Journal: November 13, 2012
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Death                              Source of Anguish (Epicurus)

Mother's 100th birthday

Over several weeks, I compiled the attached Abode PDF and backup statitistics in an Excel spreadsheet DOWNLOAD ONLY with many tables, charts and graphs of vital statistics of the Sinnock family. The data are all from my records as recorded in the Sinnock and Kin database maintained with Family Tree Maker software.

The Sinnock family is probably typical of southern England families and perhaps even for general European or even world populations with sufficient caloric intake for comfortable living. Mother died at 80 years old, a good ripe time, younger than some, older than most.

The attached PDF file summarizes information presented in more the detailed Excel file. Extracting information from the Sinnock and Kin database for these files was quite complicated. I first exported data from Family Tree Maker (FTM) in *.rtf format, after trying all others FTM export formats which were worse. Then imported the file to Word, in which I started the process of correcting numerous errors introduced by the *.rtf conversion, including: numerous errors in column assignments, unnecessary "hidden" extra lines inserted between most lines, and separation of some dates into separate columns, etc. .... Whew!!

The original data was in table format in Family Tree Maker. How they could screw up conversion is beyond me; but that was just the start. I then manually repaired the dates separted by random m,d,y cells *.rtf file, then manually separated them into full date and year only columns. Word seemed easier for such table editing than Excel. Finally after editing the table, I imported it easily to Excel.

Why FTM doesn't provide a direct import to Excel, Word, Lotus, etc. as well as just *.rtf is a mystery to me? I suggested it to them some years ago. (I learned later the CSV (comma separated variables) can be read by Excel, Lotus, and other spreadsheet programs)

I used Excel's better sorting and calculating features to generate other tables from the imported data, mixing and matching tables, eg. birth and death tables to obtain ages. Because I assigned a date to the birth of every person in the database even when no data existed and estimated death dates before 90 years, I was able to assign an age to almost everyone in the database, except those still living. There are lots of data in the Excel file, especially about age of death; Happy hunting.