pandas merge 사용법

아래 사이트에 잘 나옴

merge, join, left, right

https://www.shanelynn.ie/merge-join-dataframes-python-pandas-index-1/

# First, add the platform and device to the user usage - use a left join this time.
result = pd.merge(user_usage,
                 user_device[['use_id', 'platform', 'device']],
                 on='use_id',
                 how='left')

# At this point, the platform and device columns are included
# in the result along with all columns from user_usage

# Now, based on the "device" column in result, match the "Model" column in devices.
devices.rename(columns={"Retail Branding": "manufacturer"}, inplace=True)
result = pd.merge(result, 
                  devices[['manufacturer', 'Model']],
                  left_on='device',
                  right_on='Model',
                  how='left')
print(result.head())

 

 

 

https://www.datascienceexamples.com/joins-with-pandas/

Joins with Pandas

 

 

 

한참을 찾았습니다. Pandas 의 두 dataframe 의 차집합

 

 

df = pd.merge(dfA, dfB, on=['a','b'], how="outer", indicator=True)
df = df[df['_merge'] == 'left_only']

One liner :

df = pd.merge(dfA, dfB, on=['a','b'], how="outer", indicator=True
              ).query('_merge=="left_only"')