I have a Datafrmae with output as shown below, I am trying to extract specific text
id,value
101,*sample value as shown below*
I am trying to extract the value corresponding to key in this text
Expected output
id, key, id_new
101,Ticket-123, 1001
Given below is how the data looks like:
{
'fields': {
'status': {
'statusCategory': {
'colorName': 'yellow',
'name': 'In Progress',
'key': 'indeterminate',
'id': 4
},
'description': '',
'id': '11000',
'name': 'In Progress'
},
'summary': 'Sample Text'
},
'key': 'Ticket-123',
'id': '1001'
}
Use Series.str.get:
df['key'] = df['value'].str.get('key')
df['id_new'] = df['value'].str.get('id')
print (df)
id value key id_new
0 101 {'fields': {'status': {'statusCategory': {'col... Ticket-123 1001
Tested Dataframe:
v = {
'fields': {
'status': {
'statusCategory': {
'colorName': 'yellow',
'name': 'In Progress',
'key': 'indeterminate',
'id': 4
},
'description': '',
'id': '11000',
'name': 'In Progress'
},
'summary': 'Sample Text'
},
'key': 'Ticket-123',
'id': '1001'
}
df = pd.DataFrame({'id':101, 'value':[v]})
Related
I'm trying to build a game hiscore view with rankings for my Django site, and I'm having some issues.
The query I have is the following:
row_number_rank = Window(
expression=RowNumber(),
partition_by=[F('score_type')],
order_by=F('score').desc()
)
hiscores = Hiscore.objects.annotate(rank=row_number_rank).values()
The query above works perfectly, and properly assigns each row a rank according to how it compares to other scores within each score type.
The result of this is the following:
{ 'id': 2, 'username': 'Bob', 'score_type': 'wins', 'score': 12, 'rank': 1 }
{ 'id': 1, 'username': 'John', 'score_type': 'wins', 'score': 5, 'rank': 2 }
{ 'id': 4, 'username': 'John', 'score_type': 'kills', 'score': 37, 'rank': 1 }
{ 'id': 3, 'username': 'John', 'score_type': 'kills', 'score': 5, 'rank': 2 }
{ 'id': 5, 'username': 'Bob', 'score_type': 'kills', 'score': 2, 'rank': 3 }
The issue comes in when I want to retrieve only a specific user's scores from the above results. If I append a filter(username="Bob") the query is now:
row_number_rank = Window(
expression=RowNumber(),
partition_by=[F('score_type')],
order_by=F('score').desc()
)
hiscores = Hiscore.objects.annotate(rank=row_number_rank).filter(username='Bob').values()
Unexpectedly, adding this filter step has yielded the following incorrect results:
{ 'id': 2, 'username': 'Bob', 'score_type': 'wins', 'score': 12, 'rank': 1 }
{ 'id': 5, 'username': 'Bob', 'score_type': 'kills', 'score': 2, 'rank': 1 }
Randomly, the rank on the id=5 entry has decided to change to 1 instead of its correct value of 3.
Why would adding this filter step modify the values of the fields in the QuerySet, instead of just excluding the proper elements from it?
Thanks.
I am trying to format numbers in a Julia Dash DataTable so that they are comma separated. However, I cannot get it to work.
(name = id_name, id = id_name, format = (locale = (grouping = [3])))
I have an example below in python where they use this. Could someone show me a working example?
Source: https://dash.plotly.com/datatable/typing
app.layout = html.Div([
dash_table.DataTable(
id='typing_formatting',
data=df_typing_formatting.to_dict('records'),
columns=[{
'id': 'city',
'name': 'City',
'type': 'text'
}, {
'id': 'max',
'name': u'Max Temperature (˚F)',
'type': 'numeric',
'format': Format(
precision=0,
scheme=Scheme.fixed,
symbol=Symbol.yes,
symbol_suffix=u'˚F'
),
# equivalent manual configuration
# 'format': {
# 'locale': {
# 'symbol': ['', '˚F']
# },
# 'specifier': '$.0f'
# }
}, {
'id': 'max_date',
'name': 'Max Temperature (Date)',
'type': 'datetime'
}, {
'id': 'min',
'name': u'Min Temperature (˚F)',
'type': 'numeric',
'format': Format(
nully='N/A',
precision=0,
scheme=Scheme.fixed,
sign=Sign.parantheses,
symbol=Symbol.yes,
symbol_suffix=u'˚F'
),
# equivalent manual configuration
# 'format': {
# 'locale': {
# 'symbol': ['', '˚F']
# },
# 'nully': 'N/A'
# 'specifier': '($.0f'
# }
'on_change': {
'action': 'coerce',
'failure': 'default'
},
'validation': {
'default': None
}
}, {
'id': 'min_date',
'name': 'Min Temperature (Date)',
'type': 'datetime',
'on_change': {
'action': 'none'
}
}]
I am developing a custom module.
I tried to add it through an object button with the following code but doesn't seem to work
def create_invoice(self):
rslt = self.env['account.invoice'].create({
'partner_id': self.instructor.id,
'name': 'customer invoice',
'type': 'out_invoice',
'date_invoice': 'create_date'
})
return rslt
How can I add a button that generates an invoice?
desu
From Odoo13 there is a change in invoice object, It is now account.move instead of account.invoice.You can take this reference demo example.
invoice = self.env['account.move'].create({
'type': 'out_invoice',
'journal_id': journal.id,
'partner_id': product_id.id,
'invoice_date': date_invoice,
'date': date_invoice,
'invoice_line_ids': [(0, 0, {
'product_id': product_id.id,
'quantity': 40.0,
'name': 'product test 1',
'discount': 10.00,
'price_unit': 2.27,
})]
})
I have a Dataframe in the below format:
id, key1, key2
101, {'key': 'key_1001', 'fields': {'type': {'subtask': False}, 'summary': 'Title_1' , 'id': '71150'}}, NaN
101, NaN,{'key': 'key_1002', 'fields': {'type': {'subtask': False}, 'summary': 'Title_2' , 'id': '71151'}}
102, {'key': 'key_2001', 'fields': {'type': {'subtask': False}, 'summary': 'Title_11' , 'id': '71160'}}, NaN
102, NaN,{'key': 'key_2002', 'fields': {'type': {'subtask': False}, 'summary': 'Title_12' , 'id': '71161'}}
I am trying to achieve the below output from the above Dataframe.
id, key_value_1, key_value_2
101, key_1001, key_1002
102, key_2001, key_2002
Output of df.dict()
{'id': {103: '101', 676: '101'}, 'key1' : {103: {'fields': {'type': {'subtask': False}, 'summary': 'Title_1' , 'id': '71150'},
676: nan}
You can use:
s=df.set_index('id').stack().str.get('key').unstack()
key1 key2
id
101 key_1001 key_1002
102 key_2001 key_2002
Hello I am trying to insert one row into a table, I succesfully created the table as follows:
schema = [{'name': 'foo', 'type': 'STRING', 'mode': 'nullable'},{'name': 'bar', 'type': 'FLOAT', 'mode': 'nullable'}]
created = client.create_table(dataset='api_data_set_course_33', table='insert_test_333', schema=schema)
print('Creation Result ',created)
However when I push the row I got False,
rows = [{'id': 'NzAzYmRiY', 'one': 'uno', 'two': 'dos'}]
inserted = client.push_rows('api_data_set_course_33','insert_test_333', rows, 'id')
print('Insertion Result ',inserted)
So I don't have idea what is wrong, I really would like to appreciate support to overcome this task
This is the API that I am testing:
https://github.com/tylertreat/BigQuery-Python
This is my complete code:
schema = [{'name': 'foo', 'type': 'STRING', 'mode': 'nullable'},{'name': 'bar', 'type': 'FLOAT', 'mode': 'nullable'}]
created = client.create_table(dataset='api_data_set_course_33', table='insert_test_333', schema=schema)
print('Creation Result ',created)
rows = [{'id': 'NzAzYmRiY', 'one': 'uno', 'two': 'dos'}]
inserted = client.push_rows('api_data_set_course_33','insert_test_333', rows, 'id')
print('Insertion Result ',inserted)
Output:
Creation Result True
Insertion Result False
After feedback I tried:
>>> client = get_client(project_id, service_account=service_account,private_key_file=key, readonly=False)
>>> schema = [{'name': 'foo', 'type': 'STRING', 'mode': 'nullable'},{'name': 'bar', 'type': 'FLOAT', 'mode': 'nullable'}]
>>> rows = [{'id': 'NzAzYmRiY', 'foo': 'uno', 'bar': 'dos'}]
>>> inserted = client.push_rows('api_data_set_course_33','insert_test_333', rows, 'id')
>>> print(inserted)
False
and also:
>>> rows = [{'id': 'NzAzYmRiY', 'foo': 'uno', 'bar': 45}]
>>> inserted = client.push_rows('api_data_set_course_33','insert_test_333', rows, 'id')
>>> print(inserted)
False
However I only got false
Your row field names don't match your schema field names. Try this instead:
rows = [{'id': 'NzAzYmRiY', 'foo': 'uno', 'bar': 'dos'}]