['other', 'other', 'that', 'this', 'this'], .....: 'service': ['mail', 'web', 'mail', 'mail', 'web'], .....: 'no': [1, 2, 1, 2, 1]}).set_index(['host', 'service']) .....: In [140]: mask = df.groupby(level=0) agg('idxmax') In [141]: df_count = df.loc[mask['no']].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

['other', 'other', 'that', 'this', 'this'], .....: 'service': ['mail', 'web', 'mail', 'mail', 'web'], .....: 'no': [1, 2, 1, 2, 1]}).set_index(['host', 'service']) .....: In [140]: mask = df.groupby(level=0) agg('idxmax') In [141]: df_count = df.loc[mask['no']].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

['other', 'other', 'that', 'this', 'this'], .....: 'service': ['mail', 'web', 'mail', 'mail', 'web'], .....: 'no': [1, 2, 1, 2, 1]}).set_index(['host', 'service']) .....: In [140]: mask = df.groupby(level=0) agg('idxmax') In [141]: df_count = df.loc[mask['no']].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

['other', 'other', 'that', 'this', 'this'], .....: 'service': ['mail', 'web', 'mail', 'mail', 'web'], .....: 'no': [1, 2, 1, 2, 1]}).set_index(['host', 'service']) .....: In [140]: mask = df.groupby(level=0) powerful Python data analysis toolkit, Release 0.25.0 (continued from previous page) Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

['other', 'other', 'that', 'this', 'this'], .....: 'service': ['mail', 'web', 'mail', 'mail', 'web'], .....: 'no': [1, 2, 1, 2, 1]}).set_index(['host', 'service']) .....: In [140]: mask = df.groupby(level=0) agg('idxmax') In [141]: df_count = df.loc[mask['no']].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

"other", "that", "this", "this"], .....: "service": ["mail", "web", "mail", "mail", "web"], .....: "no": [1, 2, 1, 2, 1], .....: } .....: ).set_index(["host", "service"]) .....: In [140]: mask = df.groupby(level=0) agg("idxmax") In [141]: df_count = df.loc[mask["no"]].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 (continues on next page) 902 Chapter 2. User Guide pandas: powerful credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version

"other", "that", "this", "this"], .....: "service": ["mail", "web", "mail", "mail", "web"], .....: "no": [1, 2, 1, 2, 1], .....: } .....: ).set_index(["host", "service"]) .....: In [140]: mask = df.groupby(level=0) agg("idxmax") In [141]: df_count = df.loc[mask["no"]].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. use_bqstorage_api

"other", "that", "this", "this"], .....: "service": ["mail", "web", "mail", "mail", "web"], .....: "no": [1, 2, 1, 2, 1], .....: } .....: ).set_index(["host", "service"]) .....: In [140]: mask = df.groupby(level=0) agg("idxmax") In [141]: df_count = df.loc[mask["no"]].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google.oauth2. service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. use_bqstorage_api

"other", "that", "this", "this"], .....: "service": ["mail", "web", "mail", "mail", "web"], .....: "no": [1, 2, 1, 2, 1], .....: } .....: ).set_index(["host", "service"]) .....: In [140]: mask = df.groupby(level=0) agg("idxmax") In [141]: df_count = df.loc[mask["no"]].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 2 this mail 2 Grouping like Python’s itertools.groupby In [143]: credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google.oauth2. service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. use_bqstorage_api

"other", "that", "this", "this"], .....: "service": ["mail", "web", "mail", "mail", "web"], .....: "no": [1, 2, 1, 2, 1], .....: } .....: ).set_index(["host", "service"]) .....: In [140]: mask = df.groupby(level=0) agg("idxmax") In [141]: df_count = df.loc[mask["no"]].reset_index() In [142]: df_count Out[142]: host service no 0 other web 2 1 that mail 1 (continues on next page) 2.27. Cookbook 903 pandas: powerful credentials, such as to use Compute Engine google.auth.compute_engine.Credentials or Service Account google. oauth2.service_account.Credentials directly. New in version 0.8.0 of pandas-gbq. New in version