对于 dtype float64 的列，合并没有按预期工作

Question

I am working with two dataframes which looks like below; just small chunk of the whole data frame. The problem is if i do an inner

join using Merge function i am getting an empty result.

 DF1 COURSE_KEY CORP_ID 2.97E+11 23096 2.97E+11 23097 2.97E+11 10987 2.97E+11 560989 2.97E+11 34678 DF2 COURSE_KEY COURSE_UNIQUE_KEY COURSE_ID CERTIFICATION_ID 2.97E+11 4077 WW_13456 WFT-CK-027 2.97E+11 5789 ww_13456 NL-WFT-12121

df3 = pd.merge(Df1,Df2, on='COURSE_KEY' how='inner')

Answer 1

Merging on float values may not be the best option as float values are theoretically infinite.

For practical usage we can use int:

n = 100
df1['COURSE_KEY'] = np.round(df1.COURSE_KEY*n).astype(int) 
df2['COURSE_KEY'] = np.round(df2.COURSE_KEY*n).astype(int)

df = pd.merge(df1, df2, how = 'inner', on = 'COURSE_KEY')
df['COURSE_KEY'] = df.COURSE_KEY/n
df

Output

    COURSE_KEY  CORP_ID COURSE_UNIQUE_KEY   COURSE_ID   CERTIFICATION_ID
0   2.970000e+11    23096   4077    WW_13456    WFT-CK-027
1   2.970000e+11    23096   5789    ww_13456    NL-WFT-12121
2   2.970000e+11    23097   4077    WW_13456    WFT-CK-027
3   2.970000e+11    23097   5789    ww_13456    NL-WFT-12121
4   2.970000e+11    10987   4077    WW_13456    WFT-CK-027
5   2.970000e+11    10987   5789    ww_13456    NL-WFT-12121
6   2.970000e+11    560989  4077    WW_13456    WFT-CK-027
7   2.970000e+11    560989  5789    ww_13456    NL-WFT-12121
8   2.970000e+11    34678   4077    WW_13456    WFT-CK-027
9   2.970000e+11    34678   5789    ww_13456    NL-WFT-12121

Answer 2

It is not exactly clear what the exact issue might be, but a good guess is perhaps that there are differences in the float values. Float comparisons should be done by checking closeness and not sameness because there are often decimal variations.

Depending on the context, you might need to use a better key datatype, say an int or a string, or check for closeness, say by doing something [this answer][1] does.