Before /home/pythonscripts/mpxdatacheck/LINELIST_PAHO2024_03_18_04_53_07.csv After /home/pythonscripts/mpxdatacheck/LINELIST_PAHO2024_03_19_04_53_09.csv --------------------------- sexual_orientation --------------------------- self other diff HETERO 18.913471 21.210809 2.297338 BISEXUAL 9.660838 11.172701 1.511863 --------------------------- hospitalised --------------------------- self other diff NO 81.919003 83.503644 1.584641 --------------------------- icu --------------------------- self other diff NO 90.736458 95.230209 4.493751 --------------------------- pregnant --------------------------- Answers changed: -> Before NO 74.118371 UNK 25.697102 YUNK 0.099098 Y2 0.037589 Y3 0.030755 Y1 0.017086 Name: pregnant, dtype: float64 -> After NO 76.208629 UNK 23.594986 YUNK 0.132848 Y2 0.034656 Y1 0.017328 Y3 0.011552 Name: pregnant, dtype: float64 --------------------------- epilink --------------------------- self other diff NO 71.682636 74.913219 3.230583 --------------------------- symp_conj --------------------------- Answers changed: -> Before YES 100.0 Name: symp_conj, dtype: float64 -> After Series([], Name: symp_conj, dtype: float64) --------------------------- hiv_status --------------------------- self other diff NEG 36.569358 42.923177 6.353819 DataComPy Comparison -------------------- DataFrame Summary ----------------- DataFrame Columns Rows 0 df1 34 60902 1 df2 34 36983 Column Summary -------------- Number of columns in common: 34 Number of columns in df1 but not in df2: 0 Number of columns in df2 but not in df1: 0 Row Summary ----------- Matched on: index Any duplicates on match values: No Absolute Tolerance: 0 Relative Tolerance: 0 Number of rows in common: 36,983 Number of rows in df1 but not in df2: 23,919 Number of rows in df2 but not in df1: 0 Number of rows with some compared columns unequal: 98 Number of rows with all compared columns equal: 36,885 Column Comparison ----------------- Number of columns compared with some values unequal: 1 Number of columns compared with all values equal: 33 Total number of values which compare unequal: 98 Columns with Unequal Values or Types ------------------------------------ Column df1 dtype df2 dtype # Unequal Max Diff # Null Diff 0 symp_conj object object 98 0 98 Sample Rows with Unequal Values ------------------------------- symp_conj (df1) symp_conj (df2) recordid reporting_country BRA00003838 BRAZIL YES NaN BRA00009309 BRAZIL YES NaN BRA00009942 BRAZIL YES NaN BRA00000606 BRAZIL YES NaN BRA00002962 BRAZIL YES NaN BRA00010576 BRAZIL YES NaN BRA00009282 BRAZIL YES NaN BRA00007192 BRAZIL YES NaN BRA00010307 BRAZIL YES NaN 00001456 CHILE YES NaN Sample Rows Only in df1 (First 10 Columns) ------------------------------------------ pregnant case_class smallpox_vaccine gender sexual_orientation clade hospitalised concurrrent_sti icu outcome recordid reporting_country BRA00001923 BRAZIL NaN CONFIRMED YES MALE MSM WA NaN NO NaN A BRA00007778 BRAZIL NaN CONFIRMED NaN MALE NaN NaN NaN UNK NaN A 98308677 PANAMA NO CONFIRMED NO MALE MSM WA NO NO NO A BRA00005614 BRAZIL NaN CONFIRMED NO MALE BISEXUAL NaN NaN NO NaN NaN 6911 MEXICO NO CONFIRMED NaN MALE MSM WA NaN NaN NaN A USA00028120 UNITED STATES OF AMERICA NO NaN NO MALE NaN NaN NO NaN NaN A USA00020219 UNITED STATES OF AMERICA UNK NaN NO MALE NaN NaN NO NaN NaN A USA00007628 UNITED STATES OF AMERICA NaN NaN NaN MALE NaN NaN NO NaN NaN A BRA00007309 BRAZIL NaN CONFIRMED NaN MALE NaN NaN NaN UNK NaN A USA00022284 UNITED STATES OF AMERICA NO NaN PREV MALE NaN NaN NO CHLAM NaN A