docs/source/working-notes/troyraen/AbrilCVs/exporation_for_linea_talk.md
Exploration for LIneA talk - Dec 2, 2021
from matplotlib import pyplot as plt
import os
import pandas as pd
from astropy.coordinates import SkyCoord
from google.cloud import bigquery
import broker_utils as bu
project_id = os.getenv('GOOGLE_CLOUD_PROJECT')
dir = "/Users/troyraen/Documents/broker/Pitt-Google/troy/docs/source/working-notes/troyraen/AbrilCVs"
fcat_condensed = f"{dir}/J_MNRAS_492_L40/catalog_condensed.dat"
abrildf = pd.read_csv(fcat_condensed)
types = ('Type1', 'Type2')
fig, (ax1, ax2)= plt.subplots(1,2)
for t, ax in zip(types, (ax1, ax2)):
abrildf[t].value_counts().plot(kind='bar', ax=ax)
ax.set_title(t)
plt.show(block=False)
query = "SELECT objectId, candid, jd, fid, magpsf, sigmapsf FROM `ardent-cycling-243415.ztf_alerts.DIASource` WHERE objectId='ZTF18abcccnr'"
bq_client = bigquery.Client(project=project_id)
query_job = bq_client.query(query)
df = query_job.to_dataframe()
def query_bigquery(
query: str,
project_id: Optional[str] = None,
job_config: Optional[bigquery.job.QueryJobConfig] = None,
) -> bigquery.job.QueryJob:
"""Query BigQuery.
Example query:
``
query = (
f'SELECT * '
f'FROM `{project_id}.{dataset}.{table}` '
f'WHERE objectId={objectId} '
)
``
Example of working with the query_job:
``
for r, row in enumerate(query_job):
# row values can be accessed by field name or index
print(f"objectId={row[0]}, candid={row['candid']}")
``
"""
if project_id is None:
project_id = pgb_project_id
bq_client = bigquery.Client(project=project_id)
query_job = bq_client.query(query, job_config=job_config)
return query_job