Python/Django newcomer here. Im getting a syntax error with the following code, can anyone help me out here? IDLE3 highlights Line 16 "Treasure" just before ("Fool's Gold").
from django.shortcuts import render
# Create your views here.
def index(request):
return render(request, 'index.html', {'treasures':treasures})
class Treasure:
def __init__(self, name, value, material, location):
self.name = name
self.value = value
self.material = material
self.location = location
treasures = [
Treasure('Gold Nugget', 500.00, 'gold', "Curley's Creek, NM")
Treasure("Fool's Gold", 0, 'pyrite', "Fool's Falls, CO")
Treasure('Coffee Can', 20.00, 'tin', 'Acme, CA')
]
You forgot to put commas after the elements of the array. Like this:
treasures = [
Treasure('Gold Nugget', 500.00, 'gold', "Curley's Creek, NM"),
Treasure("Fool's Gold", 0, 'pyrite', "Fool's Falls, CO"),
Treasure('Coffee Can', 20.00, 'tin', 'Acme, CA')
]
Related
I'm looking to format data held in a df, so that it can be used in an NER model. I'm starting with the data in 2 columns, example below:
df['text'] df['annotation']
some text [('Consequence', 23, 47)]
some other text [('Consequence', 33, 46), ('Cause', 101, 150)]
And need to format it to:
TRAIN_DATA = [(some text, {'entities': [(23, 47, 'Consequence')]}), (some other text, {'entities': [(33, 46, 'Consequence'), (101, 150, 'Cause')]})
I've been attempting to iterate over each row, for example trying:
TRAIN_DATA = []
for row in df['annotation']:
entities = []
label, start, end = entity
entities.append((start, end, label))
# add to dataset
TRAIN_DATA.append((df['text'], {'entities': entities}))
However I can't get it to iterate over each row to populate the TRAIN_DATA. Sometimes there are multiple entities within the annotation column.
Grateful if anyone can highlight where I'm going wrong and how to correct it!
You can use zip() function:
TRAIN_DATA = [
(t, {"entities": [(s, e, l) for (l, s, e) in a]})
for t, a in zip(df["text"], df["annotation"])
]
print(TRAIN_DATA)
Prints:
[
("some text", {"entities": [(23, 47, "Consequence")]}),
(
"some other text",
{"entities": [(33, 46, "Consequence"), (101, 150, "Cause")]},
),
]
I am using Python 2.7 and Pandas Profiling to generate a report out of a dataframe. Following is my code:
import pandas as pd
import pandas_profiling
# the actual dataset is very large, just providing the two elements of the list
data = [{'polarity': 0.0, 'name': u'danesh bhopi', 'sentiment': 'Neutral', 'tweet_id': 1049952424818020353, 'original_tweet_id': 1049952424818020353, 'created_at': Timestamp('2018-10-10 14:18:59'), 'tweet_text': u"Wouldn't mind aus 120 all-out but before that would like to see a Finch \U0001f4af #PakVAus #AUSvPAK", 'source': u'Twitter for Android', 'location': u'pune', 'retweet_count': 0, 'geo': '', 'favorite_count': 0, 'screen_name': u'DaneshBhope'}, {'polarity': 1.0, 'name': u'kamal Kishor parihar', 'sentiment': 'Positive', 'tweet_id': 1049952403980775425, 'original_tweet_id': 1049952403980775425, 'created_at': Timestamp('2018-10-10 14:18:54'), 'tweet_text': u'#the_summer_game What you and Australia think\nPlay for\n win \nDraw\n or....! #PakvAus', 'source': u'Twitter for Android', 'location': u'chembur Mumbai ', 'retweet_count': 0, 'geo': '', 'favorite_count': 0, 'screen_name': u'kaluparihar1'}]
df = pd.DataFrame(data) #data is a python list containing python dictionaries
pfr = pandas_profiling.ProfileReport(df)
pfr.to_file("df_report.html")
The screenshot of the part of the df_report.html file is below:
As you can see in the image, the Unique(%) field in all the variables is 0.0 although the columns have unique values.
Apart from this, the chart in the 'location' variable is broken. There is no bar for the values 22, 15, 4 and the only bar is for the maximum value only. This is happening in all the variables.
Any help would be appreciated.
I am looking to upload a grouped barchart in excel, however I can't seem to find a way to do so.
Here is my code:
bar_chart2 = workbook.add_chart({'type':'column'})
bar_chart2.add_series({
'name':'Month over month product',
'categories':'=Month over month!$H$2:$H$6',
'values':'=Month over month!$I$2:$J$6',
})
bar_chart2.set_legend({'none': True})
worksheet5.insert_chart('F8',bar_chart2)
bar_chart2.set_legend({'none': True})
worksheet5.insert_chart('F8',bar_chart2)
However, I get that.
Using your provided data, I re-worked the Example given in the Docs by jmcnamara (link here) to suit what you're looking for.
Full Code:
import pandas as pd
import xlsxwriter
headings = [' ', 'Apr 2017', 'May 2017']
data = [
['NGN', 'UGX', 'KES', 'TZS', 'CNY'],
[5816, 1121, 115, 146, 1],
[7089, 1095, 226, 120, 0],
]
#opening workbook
workbook = xlsxwriter.Workbook("test.xlsx")
worksheet5 = workbook.add_worksheet('Month over month')
worksheet5.write_row('H1', headings)
worksheet5.write_column('H2', data[0])
worksheet5.write_column('I2', data[1])
worksheet5.write_column('J2', data[2])
# beginning of OP snippet
bar_chart2 = workbook.add_chart({'type':'column'})
bar_chart2.add_series({
'name': "='Month over month'!$I$1",
'categories': "='Month over month'!$H$2:$H$6",
'values': "='Month over month'!$I$2:$I$6",
})
bar_chart2.add_series({
'name': "='Month over month'!$J$1",
'categories': "='Month over month'!$H$2:$H$6",
'values': "='Month over month'!$J$2:$J$6",
})
bar_chart2.set_title ({'name': 'Month over month product'})
bar_chart2.set_style(11)
#I took the liberty of leaving the legend in there - it was commented in originally
#bar_chart2.set_legend({'none': True})
# end of OP snippet
worksheet5.insert_chart('F8', bar_chart2)
workbook.close()
Output:
Using the commits from breznak for the encoders (I wasn't able to figure out "git checkout ..." with GitHub, so I just carefully copied over the three files - base.py, multi.py, and multi_test.py).
I ran multi_test.py without any problems.
Then I adjusted my model parameters (MODEL_PARAMS), so that the encoders portion of 'sensorParams' looks like this:
'encoders': {
'frequency': {
'fieldname': u'frequency',
'type': 'SimpleVector',
'length': 5,
'minVal': 0,
'maxVal': 210
}
},
I also adjusted the modelInput portion of my code, so it looked like this:
model = ModelFactory.create(model_params.MODEL_PARAMS)
model.enableInference({'predictedField': 'frequency'})
y = [1,2,3,4,5]
modelInput = {"frequency": y}
result = model.run(modelInput)
But I get the final error, regardless if I instantiate 'y' as a list or a numpy.ndarray
File "nta/eng/lib/python2.7/site-packages/nupic/encoders/base.py", line 183, in _getInputValue
return getattr(obj, fieldname)
AttributeError: 'list' object has no attribute 'idx0'
I also tried initializing a SimpleVector encoder inline with my modelInput, directly encoding my array, then passing it through modelInput. That violated the input parameters of my SimpleVector, because I was now double encoding. So I removed the encoders portion of my model parameters dictionary. That caused a spit up, because some part of my model was looking for that portion of the dictionary.
Any suggestions on what I should do next?
Edit: Here're the files I'm using with the OPF.
sendAnArray.py
import numpy
from nupic.frameworks.opf.modelfactory import ModelFactory
import model_params
class sendAnArray():
def __init__(self):
self.model = ModelFactory.create(model_params.MODEL_PARAMS)
self.model.enableInference({'predictedField': 'frequency'})
for i in range(100):
self.run()
def run(self):
y = [1,2,3,4,5]
modelInput = {"frequency": y}
result = self.model.run(modelInput)
anomalyScore = result.inferences['anomalyScore']
print y, anomalyScore
sAA = sendAnArray()
model_params.py
MODEL_PARAMS = {
'model': "CLA",
'version': 1,
'predictAheadTime': None,
'modelParams': {
'inferenceType': 'TemporalAnomaly',
'sensorParams': {
'verbosity' : 0,
'encoders': {
'frequency': {
'fieldname': u'frequency',
'type': 'SimpleVector',
'length': 5,
'minVal': 0,
'maxVal': 210
}
},
'sensorAutoReset' : None,
},
'spEnable': True,
'spParams': {
'spVerbosity' : 0,
'globalInhibition': 1,
'columnCount': 2048,
'inputWidth': 5,
'numActivePerInhArea': 60,
'seed': 1956,
'coincInputPoolPct': 0.5,
'synPermConnected': 0.1,
'synPermActiveInc': 0.1,
'synPermInactiveDec': 0.01,
},
'tpEnable' : True,
'tpParams': {
'verbosity': 0,
'columnCount': 2048,
'cellsPerColumn': 32,
'inputWidth': 2048,
'seed': 1960,
'temporalImp': 'cpp',
'newSynapseCount': 20,
'maxSynapsesPerSegment': 32,
'maxSegmentsPerCell': 128,
'initialPerm': 0.21,
'permanenceInc': 0.1,
'permanenceDec' : 0.1,
'globalDecay': 0.0,
'maxAge': 0,
'minThreshold': 12,
'activationThreshold': 16,
'outputType': 'normal',
'pamLength': 1,
},
'clParams': {
'regionName' : 'CLAClassifierRegion',
'clVerbosity' : 0,
'alpha': 0.0001,
'steps': '5',
},
'anomalyParams': {
u'anomalyCacheRecords': None,
u'autoDetectThreshold': None,
u'autoDetectWaitRecords': 2184
},
'trainSPNetOnlyIfRequested': False,
},
}
The problem seems to be that the SimpleVector class is accepting an array instead of a dict as its input, and then reconstructs that internally as {'list': {'idx0': 1, 'idx1': 2, ...}} (ie as if this dict had been the input). This is fine if it is done consistently, but your error shows that it's broken down somewhere. Have a word with #breznak about this.
Working through the OPF was difficult. I wanted to input an array of indices into the temporal pooler, so I opted to interface directly with the algorithms (I relied heavy on hello_tp.py). I ignored SimpleVector all together, and instead worked through the BitmapArray encoder.
Subutai has a useful email on the nupic-discuss listserve, where he breaks down the three main areas of the NuPIC API: algorithms, networks/regions, & the OPF. That helped me understand my options better.
If I set the format of the first column in a ListCtrl to align centre (or align right) nothing happens. It works for the other columns.
This only happens on Windows - I have tested it on Linux and it works fine.
Does anyone know if there is a work-round or other solution?
Here is an example based on code found at http://zetcode.com/wxpython/
import wx
import sys
packages = [('jessica alba', 'pomona', '1981'), ('sigourney weaver', 'new york', '1949'),
('angelina jolie', 'los angeles', '1975'), ('natalie portman', 'jerusalem', '1981'),
('rachel weiss', 'london', '1971'), ('scarlett johansson', 'new york', '1984' )]
class Actresses(wx.Frame):
def __init__(self, parent, id, title):
wx.Frame.__init__(self, parent, id, title, size=(380, 230))
hbox = wx.BoxSizer(wx.HORIZONTAL)
panel = wx.Panel(self, -1)
self.list = wx.ListCtrl(panel, -1, style=wx.LC_REPORT)
self.list.InsertColumn(0, 'name', wx.LIST_FORMAT_CENTRE,width=140)
self.list.InsertColumn(1, 'place', wx.LIST_FORMAT_CENTRE,width=130)
self.list.InsertColumn(2, 'year', wx.LIST_FORMAT_CENTRE, 90)
for i in packages:
index = self.list.InsertStringItem(sys.maxint, i[0])
self.list.SetStringItem(index, 1, i[1])
self.list.SetStringItem(index, 2, i[2])
hbox.Add(self.list, 1, wx.EXPAND)
panel.SetSizer(hbox)
self.Centre()
self.Show(True)
app = wx.App()
Actresses(None, -1, 'actresses')
app.MainLoop()
I have found that this works (notice I start inserting the columns at 1 rather than 0):
self.list = wx.ListCtrl(panel, -1, style=wx.LC_REPORT)
self.list.InsertColumn(1, 'name', wx.LIST_FORMAT_CENTRE,width=140)
self.list.InsertColumn(2, 'place', wx.LIST_FORMAT_CENTRE,width=130)
self.list.InsertColumn(3, 'year', wx.LIST_FORMAT_CENTRE, 90)
Not sure why this works, but it does. Hopefully, there will be no repercussions from doing this.
Thanks to robots.jpg for inspiring the idea.
Windows definitely treats the first column differently. One workaround is to create an empty column 0 and hide it:
class Actresses(wx.Frame):
def __init__(self, parent, id, title):
wx.Frame.__init__(self, parent, id, title, size=(380, 230))
#...
self.list = wx.ListCtrl(panel, -1, style=wx.LC_REPORT)
self.list.InsertColumn(0, '', width=0)
self.list.InsertColumn(1, 'name', wx.LIST_FORMAT_CENTRE,width=140)
self.list.InsertColumn(2, 'place', wx.LIST_FORMAT_CENTRE,width=130)
self.list.InsertColumn(3, 'year', wx.LIST_FORMAT_CENTRE, width=90)
for i in packages:
index = self.list.InsertStringItem(sys.maxint, '')
self.list.SetStringItem(index, 1, i[0])
self.list.SetStringItem(index, 2, i[1])
self.list.SetStringItem(index, 3, i[2])
# catch resize event
self.list.Bind(wx.EVT_LIST_COL_BEGIN_DRAG, self.OnColDrag)
#...
def OnColDrag(self, evt):
if evt.m_col == 0:
evt.Veto()
I can't think of any major side-effects from doing this, but let me know if I'm wrong. I guess GetItemText() or anything else that assumes there is useful data in the first column would no longer be useful.
Edit - added code to prevent resizing column 0.