Before /home/pythonscripts/mpxdatacheck/LINELIST_PAHO2024_03_19_04_53_09.csv After /home/pythonscripts/mpxdatacheck/LINELIST_PAHO2024_03_20_04_53_31.csv --------------------------- sexual_orientation --------------------------- self other diff MSM 62.047462 66.703623 4.656161 --------------------------- hospitalised --------------------------- self other diff UNK 8.445958 9.490746 1.044788 --------------------------- icu --------------------------- self other diff UNK 4.372309 8.776628 4.404319 --------------------------- pregnant --------------------------- Answers changed: -> Before NO 76.208629 UNK 23.594986 YUNK 0.132848 Y2 0.034656 Y1 0.017328 Y3 0.011552 Name: pregnant, dtype: float64 -> After NO 74.118371 UNK 25.697102 YUNK 0.099098 Y2 0.037589 Y3 0.030755 Y1 0.017086 Name: pregnant, dtype: float64 --------------------------- epilink --------------------------- self other diff YES 21.033868 23.690773 2.656905 --------------------------- symp_conj --------------------------- Answers changed: -> Before Series([], Name: symp_conj, dtype: float64) -> After YES 100.0 Name: symp_conj, dtype: float64 --------------------------- hiv_status --------------------------- self other diff UNK 5.9375 12.297161 6.359661 DataComPy Comparison -------------------- DataFrame Summary ----------------- DataFrame Columns Rows 0 df1 34 36983 1 df2 34 60902 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: 0 Number of rows in df2 but not in df1: 23,919 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 19 ECUADOR NaN YES BRA00008622 BRAZIL NaN YES 00001456 CHILE NaN YES 00000313 CHILE NaN YES BRA00008928 BRAZIL NaN YES BRA00010307 BRAZIL NaN YES BRA00009309 BRAZIL NaN YES BRA00002205 BRAZIL NaN YES BRA00006579 BRAZIL NaN YES BRA00000807 BRAZIL NaN YES Sample Rows Only in df2 (First 10 Columns) ------------------------------------------ pregnant case_class smallpox_vaccine gender sexual_orientation clade hospitalised concurrrent_sti icu outcome recordid reporting_country USA00030637 UNITED STATES OF AMERICA UNK NaN NO MALE NaN NaN NO NaN NaN A USA00008370 UNITED STATES OF AMERICA NaN NaN NO MALE NaN NaN NO NaN NaN A 58 EL SALVADOR NaN CONFIRMED NO MALE MSM NaN NO NO NO A USA00021617 UNITED STATES OF AMERICA NaN NaN NaN MALE NaN NaN NO NaN NaN A USA00025686 UNITED STATES OF AMERICA NO NaN PREV MALE NaN NaN NO NaN NaN A USA00027129 UNITED STATES OF AMERICA UNK NaN PREV MALE NaN NaN NO NaN NaN A USA00004252 UNITED STATES OF AMERICA NaN NaN UNK MALE NaN NaN UNK NaN NaN NaN 1114 ARGENTINA NO CONFIRMED NaN MALE NaN NaN NO NaN NO A USA00028176 UNITED STATES OF AMERICA NaN NaN UNK MALE NaN NaN NO CHLAM NaN A 00000953 CHILE NO CONFIRMED UNK MALE O NaN YISOL NaN NaN NaN