I have the following two dataframes (samples). I’d like to know which companies had their sales changed between the two dataframes. For example, AAPL is different in the second dataframe.
Sales 52W High 52W Low Root A 4.81B -0.1072 0.1082 AA 12.81B -0.3124 0.0709 AABA 266.05M -0.2038 0.0437 AAL 43.52B -0.3285 0.1131 AAN 3.61B -0.0208 0.4716 AAOI 321.80M -0.5196 0.5195 AAP 9.42B -0.0153 1.1190 AAPL 255.27B -0.0101 0.5210 AAXN 385.40M -0.1005 2.3432 ABB 35.52B -0.1870 0.0987 Sales 52W High 52W Low Root A 4.81B -0.1019 0.1149 AA 12.81B -0.3527 0.0082 AABA 266.05M -0.2212 0.0208 AAL 43.52B -0.3487 0.0797 AAN 3.61B -0.0196 0.4733 AAOI 321.80M -0.5478 0.4303 AAP 9.42B -0.0216 1.1218 AAPL 243.89B -0.0286 0.4957 AAXN 385.40M -0.0806 2.4171 ABB 35.52B -0.1838 0.1030
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Answer
This you can using ne
(not equal)
df1.Sales.ne(df2.Sales)# the one mask as True is the different Out[482]: Root A False AA False AABA False AAL False AAN False AAOI False AAP False AAPL True AAXN False ABB False Name: Sales, dtype: bool