> For the complete documentation index, see [llms.txt](https://antoinepinto.gitbook.io/easyenvi/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://antoinepinto.gitbook.io/easyenvi/google-cloud-environment/big-query-operations/easyenvi.gcloud.bq.write.md).

# easyenvi.gcloud.BQ.write

Write an entire Python dataframe into Big Query.

#### Parameters

* **obj : *****pandas.DataFrame***\
  table to save
* **path : *****str***\
  path representing the data set and the name of the table (ex : "mydata.mytable")
* **schema : *****list (optional)***\
  schema of the table. If not specified, a schema is generated based on mapping

  Format: list of dictionnaries (see below example or [Google Cloud Documentation](https://cloud.google.com/bigquery/docs/schemas#creating_a_JSON_schema_file))

#### Examples

```python
schema = [{"name": "country",   "type": "STRING"},
          {"name": "date",      "type": "TIMESTAMP"},
          {"name": "inflation", "type": "FLOAT"}]

envi.GCP.BQ.write(obj=inflation, path='finance_data.inflation', schema=schema)
```