Pd Merge Pandas Merge Examples

  rfm_df = pd.merge(recency_df, frequency_df, how='left', on='CustomerID')
rfm_df = pd.merge(rfm_df, monetary_df, how='left', on='CustomerID')
rfm_df.head() 
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  epss_kev = pd.merge(cisa_df, epss, left_on='CVE', right_on='CVE')
epss_kev_nvd =  pd.merge(epss_kev, nvd, left_on='CVE', right_on='CVE')
epss_kev_nvd =  epss_kev_nvd[["CVE", "CVSS3", "EPSS", "Description"]] 
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  factCovid = pd.merge(factCovid1, factCovid2, on='fips', how='inner') 
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  result = pd.merge(left, right, on=["key1", "key2"])
result 
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  train_and_test = pd.merge(train_and_test, sample, on="id", how="inner") 
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  #(Write code here)
merged_dfs = pd.merge(umbc2,jhu2)
merged_dfs.head() 
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  movies_df_v10 = pd.merge(movies_df_v2, best_directors, how='left', on='top_director') 
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  movies_df_v4 = pd.merge(movies_df_v3, number_of_oscar_wins_per_star_1, how='left', on='top_star_1')
 
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  df_merge = pd.merge(hisdf, ndf, how='inner', on='Date')
df_merge 
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  result = pd.merge(left, right, how="left", on=["key1", "key2"])
result 
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  result = pd.merge(left, right, how="outer", on=["key1", "key2"])
result 
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