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Closes 18. Fixed bug in Pandas and PySpark deserialization.
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‎CHANGES.rst‎

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Release 1.0.0-rc2
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=========================================
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* Closed #18. Fixed bug where loading data from a Pandas Dataframe could produce data points with None values.
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* Added ``HighchartsPandasDeserializationError`` and ``HighchartsPySparkDeserializationError``.
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---------------
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19
Release 1.0.0-rc1
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=========================================
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‎docs/errors.rst‎

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@@ -134,6 +134,30 @@ HighchartsCSVDeserializationError (from :class:`ValueError <python:ValueError>`)
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--------------
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HighchartsPandasDeserializationError (from :class:`ValueError <python:ValueError>`)
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==========================================================================================
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.. autoexception:: HighchartsPandasDeserializationError
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.. collapse:: Class Inheritance
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.. inheritance-diagram:: HighchartsPandasDeserializationError
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:parts: -1
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--------------
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HighchartsPySparkDeserializationError (from :class:`ValueError <python:ValueError>`)
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==========================================================================================
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.. autoexception:: HighchartsPySparkDeserializationError
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.. collapse:: Class Inheritance
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.. inheritance-diagram:: HighchartsPySparkDeserializationError
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:parts: -1
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--------------
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HighchartsMissingKeyError (from :class:`ValueError <python:ValueError>`)
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==========================================================================================
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‎highcharts_core/__version__.py‎

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__version__ = '1.0.0-rc1'
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__version__ = '1.0.0-rc2'

‎highcharts_core/errors.py‎

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@@ -56,6 +56,18 @@ class HighchartsCSVDeserializationError(HighchartsError):
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pass
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class HighchartsPandasDeserializationError(HighchartsError):
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""":exc:`ValueError <python:ValueError>` encountered when Highcharts for Python is
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unable to properly deserialize Pandas data."""
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pass
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class HighchartsPySparkDeserializationError(HighchartsError):
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""":exc:`ValueError <python:ValueError>` encountered when Highcharts for Python is
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unable to properly deserialize PySpark data."""
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pass
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class HighchartsMissingKeyError(HighchartsParseError):
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""":exc:`ValueError <python:ValueError>` encountered when Highcharts for Python
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encounters a missing key when parsing a JavaScript object literal."""

‎highcharts_core/options/series/base.py‎

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@@ -696,6 +696,9 @@ def load_from_pandas(self,
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raise errors.HighchartsValueError(f'df is expected to be a pandas DataFrame '
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f'or Series. Was: {df.__class__.__name__}')
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if not property_map:
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raise errors.HighchartsValueError('property_map cannot be None or empty')
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property_map = validators.dict(property_map)
700703
for key in property_map:
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map_value = property_map[key]
@@ -712,9 +715,9 @@ def load_from_pandas(self,
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record_as_dict = {}
713716
for key in property_map:
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map_value = property_map[key]
715-
record_as_dict[key] = record_as_dict.get(map_value, None)
718+
record_as_dict[key] = record.get(map_value, None)
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records_as_dicts.append(record_as_dict)
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self.data = records_as_dicts
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@classmethod
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record_as_dict = {}
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for key in property_map:
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map_value = property_map[key]
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record_as_dict[key] = record_as_dict.get(map_value, None)
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record_as_dict[key] = record.get(map_value, None)
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records_as_dicts.append(record_as_dict)
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self.data = records_as_dicts

‎tests/input_files/test-data-files/nst-est2019-01.csv‎

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@@ -4,61 +4,55 @@ Northeast,"55,380,134","55,604,223","55,775,216","55,901,806","56,006,011","56,0
44
Midwest,"66,974,416","67,157,800","67,336,743","67,560,379","67,745,167","67,860,583","67,987,540","68,126,781","68,236,628","68,329,004"
55
South,"114,866,680","116,006,522","117,241,208","118,364,400","119,624,037","120,997,341","122,351,760","123,542,189","124,569,433","125,580,448"
66
West,"72,100,436","72,788,329","73,477,823","74,167,130","74,925,793","75,742,555","76,559,681","77,257,329","77,834,820","78,347,268"
7-
.Alabama,"4,785,437","4,799,069","4,815,588","4,830,081","4,841,799","4,852,347","4,863,525","4,874,486","4,887,681","4,903,185"
8-
.Alaska,"713,910","722,128","730,443","737,068","736,283","737,498","741,456","739,700","735,139","731,545"
9-
.Arizona,"6,407,172","6,472,643","6,554,978","6,632,764","6,730,413","6,829,676","6,941,072","7,044,008","7,158,024","7,278,717"
10-
.Arkansas,"2,921,964","2,940,667","2,952,164","2,959,400","2,967,392","2,978,048","2,989,918","3,001,345","3,009,733","3,017,804"
11-
.California,"37,319,502","37,638,369","37,948,800","38,260,787","38,596,972","38,918,045","39,167,117","39,358,497","39,461,588","39,512,223"
12-
.Colorado,"5,047,349","5,121,108","5,192,647","5,269,035","5,350,101","5,450,623","5,539,215","5,611,885","5,691,287","5,758,736"
13-
.Connecticut,"3,579,114","3,588,283","3,594,547","3,594,841","3,594,524","3,587,122","3,578,141","3,573,297","3,571,520","3,565,287"
14-
.Delaware,"899,593","907,381","915,179","923,576","932,487","941,252","948,921","956,823","965,479","973,764"
15-
.District of Columbia,"605,226","619,800","634,924","650,581","662,328","675,400","685,815","694,906","701,547","705,749"
16-
.Florida,"18,845,537","19,053,237","19,297,822","19,545,621","19,845,911","20,209,042","20,613,477","20,963,613","21,244,317","21,477,737"
17-
.Georgia,"9,711,881","9,802,431","9,901,430","9,972,479","10,067,278","10,178,447","10,301,890","10,410,330","10,511,131","10,617,423"
18-
.Hawaii,"1,363,963","1,379,329","1,394,804","1,408,243","1,414,538","1,422,052","1,427,559","1,424,393","1,420,593","1,415,872"
19-
.Idaho,"1,570,746","1,583,910","1,595,324","1,611,206","1,631,112","1,651,059","1,682,380","1,717,715","1,750,536","1,787,065"
20-
.Illinois,"12,840,503","12,867,454","12,882,510","12,895,129","12,884,493","12,858,913","12,820,527","12,778,828","12,723,071","12,671,821"
21-
.Indiana,"6,490,432","6,516,528","6,537,703","6,568,713","6,593,644","6,608,422","6,634,304","6,658,078","6,695,497","6,732,219"
22-
.Iowa,"3,050,745","3,066,336","3,076,190","3,092,997","3,109,350","3,120,960","3,131,371","3,141,550","3,148,618","3,155,070"
23-
.Kansas,"2,858,190","2,869,225","2,885,257","2,893,212","2,900,475","2,909,011","2,910,844","2,908,718","2,911,359","2,913,314"
24-
.Kentucky,"4,348,181","4,369,821","4,386,346","4,404,659","4,414,349","4,425,976","4,438,182","4,452,268","4,461,153","4,467,673"
25-
.Louisiana,"4,544,532","4,575,625","4,600,972","4,624,527","4,644,013","4,664,628","4,678,135","4,670,560","4,659,690","4,648,794"
26-
.Maine,"1,327,629","1,328,284","1,327,729","1,328,009","1,330,513","1,328,262","1,331,317","1,334,612","1,339,057","1,344,212"
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.Maryland,"5,788,645","5,839,419","5,886,992","5,923,188","5,957,283","5,985,562","6,003,323","6,023,868","6,035,802","6,045,680"
28-
.Massachusetts,"6,566,307","6,613,583","6,663,005","6,713,315","6,762,596","6,794,228","6,823,608","6,859,789","6,882,635","6,892,503"
29-
.Michigan,"9,877,510","9,882,412","9,897,145","9,913,065","9,929,848","9,931,715","9,950,571","9,973,114","9,984,072","9,986,857"
30-
.Minnesota,"5,310,828","5,346,143","5,376,643","5,413,479","5,451,079","5,482,032","5,522,744","5,566,230","5,606,249","5,639,632"
31-
.Mississippi,"2,970,548","2,978,731","2,983,816","2,988,711","2,990,468","2,988,471","2,987,938","2,988,510","2,981,020","2,976,149"
32-
.Missouri,"5,995,974","6,010,275","6,024,367","6,040,715","6,056,202","6,071,732","6,087,135","6,106,670","6,121,623","6,137,428"
33-
.Montana,"990,697","997,316","1,003,783","1,013,569","1,021,869","1,030,475","1,040,859","1,052,482","1,060,665","1,068,778"
34-
.Nebraska,"1,829,542","1,840,672","1,853,303","1,865,279","1,879,321","1,891,277","1,905,616","1,915,947","1,925,614","1,934,408"
35-
.Nevada,"2,702,405","2,712,730","2,743,996","2,775,970","2,817,628","2,866,939","2,917,563","2,969,905","3,027,341","3,080,156"
36-
.New Hampshire,"1,316,762","1,320,202","1,324,232","1,326,622","1,333,341","1,336,350","1,342,307","1,348,787","1,353,465","1,359,711"
37-
.New Jersey,"8,799,446","8,828,117","8,844,942","8,856,972","8,864,525","8,867,949","8,870,827","8,885,525","8,886,025","8,882,190"
38-
.New Mexico,"2,064,552","2,080,450","2,087,309","2,092,273","2,089,568","2,089,291","2,091,630","2,091,784","2,092,741","2,096,829"
39-
.New York,"19,399,878","19,499,241","19,572,932","19,624,447","19,651,049","19,654,666","19,633,428","19,589,572","19,530,351","19,453,561"
40-
.North Carolina,"9,574,323","9,657,592","9,749,476","9,843,336","9,932,887","10,031,646","10,154,788","10,268,233","10,381,615","10,488,084"
41-
.North Dakota,"674,715","685,225","701,176","722,036","737,401","754,066","754,434","754,942","758,080","762,062"
42-
.Ohio,"11,539,336","11,544,663","11,548,923","11,576,684","11,602,700","11,617,527","11,634,370","11,659,650","11,676,341","11,689,100"
43-
.Oklahoma,"3,759,944","3,788,379","3,818,814","3,853,214","3,878,187","3,909,500","3,926,331","3,931,316","3,940,235","3,956,971"
44-
.Oregon,"3,837,491","3,872,036","3,899,001","3,922,468","3,963,244","4,015,792","4,089,976","4,143,625","4,181,886","4,217,737"
45-
.Pennsylvania,"12,711,160","12,745,815","12,767,118","12,776,309","12,788,313","12,784,826","12,782,275","12,787,641","12,800,922","12,801,989"
46-
.Rhode Island,"1,053,959","1,053,649","1,054,621","1,055,081","1,055,936","1,056,065","1,056,770","1,055,673","1,058,287","1,059,361"
47-
.South Carolina,"4,635,649","4,671,994","4,717,354","4,764,080","4,823,617","4,891,938","4,957,968","5,021,268","5,084,156","5,148,714"
48-
.South Dakota,"816,166","823,579","833,566","842,316","849,129","853,988","862,996","872,868","878,698","884,659"
49-
.Tennessee,"6,355,311","6,399,291","6,453,898","6,494,340","6,541,223","6,591,170","6,646,010","6,708,799","6,771,631","6,829,174"
50-
.Texas,"25,241,971","25,645,629","26,084,481","26,480,266","26,964,333","27,470,056","27,914,410","28,295,273","28,628,666","28,995,881"
51-
.Utah,"2,775,332","2,814,384","2,853,375","2,897,640","2,936,879","2,981,835","3,041,868","3,101,042","3,153,550","3,205,958"
52-
.Vermont,"625,879","627,049","626,090","626,210","625,214","625,216","623,657","624,344","624,358","623,989"
53-
.Virginia,"8,023,699","8,101,155","8,185,080","8,252,427","8,310,993","8,361,808","8,410,106","8,463,587","8,501,286","8,535,519"
54-
.Washington,"6,742,830","6,826,627","6,897,058","6,963,985","7,054,655","7,163,657","7,294,771","7,423,362","7,523,869","7,614,893"
55-
.West Virginia,"1,854,239","1,856,301","1,856,872","1,853,914","1,849,489","1,842,050","1,831,023","1,817,004","1,804,291","1,792,147"
56-
.Wisconsin,"5,690,475","5,705,288","5,719,960","5,736,754","5,751,525","5,760,940","5,772,628","5,790,186","5,807,406","5,822,434"
57-
.Wyoming,"564,487","567,299","576,305","582,122","582,531","585,613","584,215","578,931","577,601","578,759"
58-
,,,,,,,,,,
59-
Puerto Rico,"3,721,525","3,678,732","3,634,488","3,593,077","3,534,874","3,473,232","3,406,672","3,325,286","3,193,354","3,193,694"
60-
"Note: The estimates are based on the 2010 Census and reflect changes to the April 1, 2010 population due to the Count Question Resolution program and geographic program revisions. See Geographic Terms and Definitions at http://www.census.gov/programs-surveys/popest/guidance-geographies/terms-and-definitions.html for a list of the states that are included in each region. All geographic boundaries for the 2019 population estimates series except statistical area delineations are as of January 1, 2019. For population estimates methodology statements, see http://www.census.gov/programs-surveys/popest/technical-documentation/methodology.html.",,,,,,,,,,
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Suggested Citation:,,,,,,,,,,
62-
"Table 1. Annual Estimates of the Resident Population for the United States, Regions, States, and Puerto Rico: April 1, 2010 to July 1, 2019 (NST-EST2019-01)",,,,,,,,,,
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"Source: U.S. Census Bureau, Population Division",,,,,,,,,,
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Release Date: December 2019,,,,,,,,,,
7+
Alabama,"4,785,437","4,799,069","4,815,588","4,830,081","4,841,799","4,852,347","4,863,525","4,874,486","4,887,681","4,903,185"
8+
Alaska,"713,910","722,128","730,443","737,068","736,283","737,498","741,456","739,700","735,139","731,545"
9+
Arizona,"6,407,172","6,472,643","6,554,978","6,632,764","6,730,413","6,829,676","6,941,072","7,044,008","7,158,024","7,278,717"
10+
Arkansas,"2,921,964","2,940,667","2,952,164","2,959,400","2,967,392","2,978,048","2,989,918","3,001,345","3,009,733","3,017,804"
11+
California,"37,319,502","37,638,369","37,948,800","38,260,787","38,596,972","38,918,045","39,167,117","39,358,497","39,461,588","39,512,223"
12+
Colorado,"5,047,349","5,121,108","5,192,647","5,269,035","5,350,101","5,450,623","5,539,215","5,611,885","5,691,287","5,758,736"
13+
Connecticut,"3,579,114","3,588,283","3,594,547","3,594,841","3,594,524","3,587,122","3,578,141","3,573,297","3,571,520","3,565,287"
14+
Delaware,"899,593","907,381","915,179","923,576","932,487","941,252","948,921","956,823","965,479","973,764"
15+
District of Columbia,"605,226","619,800","634,924","650,581","662,328","675,400","685,815","694,906","701,547","705,749"
16+
Florida,"18,845,537","19,053,237","19,297,822","19,545,621","19,845,911","20,209,042","20,613,477","20,963,613","21,244,317","21,477,737"
17+
Georgia,"9,711,881","9,802,431","9,901,430","9,972,479","10,067,278","10,178,447","10,301,890","10,410,330","10,511,131","10,617,423"
18+
Hawaii,"1,363,963","1,379,329","1,394,804","1,408,243","1,414,538","1,422,052","1,427,559","1,424,393","1,420,593","1,415,872"
19+
Idaho,"1,570,746","1,583,910","1,595,324","1,611,206","1,631,112","1,651,059","1,682,380","1,717,715","1,750,536","1,787,065"
20+
Illinois,"12,840,503","12,867,454","12,882,510","12,895,129","12,884,493","12,858,913","12,820,527","12,778,828","12,723,071","12,671,821"
21+
Indiana,"6,490,432","6,516,528","6,537,703","6,568,713","6,593,644","6,608,422","6,634,304","6,658,078","6,695,497","6,732,219"
22+
Iowa,"3,050,745","3,066,336","3,076,190","3,092,997","3,109,350","3,120,960","3,131,371","3,141,550","3,148,618","3,155,070"
23+
Kansas,"2,858,190","2,869,225","2,885,257","2,893,212","2,900,475","2,909,011","2,910,844","2,908,718","2,911,359","2,913,314"
24+
Kentucky,"4,348,181","4,369,821","4,386,346","4,404,659","4,414,349","4,425,976","4,438,182","4,452,268","4,461,153","4,467,673"
25+
Louisiana,"4,544,532","4,575,625","4,600,972","4,624,527","4,644,013","4,664,628","4,678,135","4,670,560","4,659,690","4,648,794"
26+
Maine,"1,327,629","1,328,284","1,327,729","1,328,009","1,330,513","1,328,262","1,331,317","1,334,612","1,339,057","1,344,212"
27+
Maryland,"5,788,645","5,839,419","5,886,992","5,923,188","5,957,283","5,985,562","6,003,323","6,023,868","6,035,802","6,045,680"
28+
Massachusetts,"6,566,307","6,613,583","6,663,005","6,713,315","6,762,596","6,794,228","6,823,608","6,859,789","6,882,635","6,892,503"
29+
Michigan,"9,877,510","9,882,412","9,897,145","9,913,065","9,929,848","9,931,715","9,950,571","9,973,114","9,984,072","9,986,857"
30+
Minnesota,"5,310,828","5,346,143","5,376,643","5,413,479","5,451,079","5,482,032","5,522,744","5,566,230","5,606,249","5,639,632"
31+
Mississippi,"2,970,548","2,978,731","2,983,816","2,988,711","2,990,468","2,988,471","2,987,938","2,988,510","2,981,020","2,976,149"
32+
Missouri,"5,995,974","6,010,275","6,024,367","6,040,715","6,056,202","6,071,732","6,087,135","6,106,670","6,121,623","6,137,428"
33+
Montana,"990,697","997,316","1,003,783","1,013,569","1,021,869","1,030,475","1,040,859","1,052,482","1,060,665","1,068,778"
34+
Nebraska,"1,829,542","1,840,672","1,853,303","1,865,279","1,879,321","1,891,277","1,905,616","1,915,947","1,925,614","1,934,408"
35+
Nevada,"2,702,405","2,712,730","2,743,996","2,775,970","2,817,628","2,866,939","2,917,563","2,969,905","3,027,341","3,080,156"
36+
New Hampshire,"1,316,762","1,320,202","1,324,232","1,326,622","1,333,341","1,336,350","1,342,307","1,348,787","1,353,465","1,359,711"
37+
New Jersey,"8,799,446","8,828,117","8,844,942","8,856,972","8,864,525","8,867,949","8,870,827","8,885,525","8,886,025","8,882,190"
38+
New Mexico,"2,064,552","2,080,450","2,087,309","2,092,273","2,089,568","2,089,291","2,091,630","2,091,784","2,092,741","2,096,829"
39+
New York,"19,399,878","19,499,241","19,572,932","19,624,447","19,651,049","19,654,666","19,633,428","19,589,572","19,530,351","19,453,561"
40+
North Carolina,"9,574,323","9,657,592","9,749,476","9,843,336","9,932,887","10,031,646","10,154,788","10,268,233","10,381,615","10,488,084"
41+
North Dakota,"674,715","685,225","701,176","722,036","737,401","754,066","754,434","754,942","758,080","762,062"
42+
Ohio,"11,539,336","11,544,663","11,548,923","11,576,684","11,602,700","11,617,527","11,634,370","11,659,650","11,676,341","11,689,100"
43+
Oklahoma,"3,759,944","3,788,379","3,818,814","3,853,214","3,878,187","3,909,500","3,926,331","3,931,316","3,940,235","3,956,971"
44+
Oregon,"3,837,491","3,872,036","3,899,001","3,922,468","3,963,244","4,015,792","4,089,976","4,143,625","4,181,886","4,217,737"
45+
Pennsylvania,"12,711,160","12,745,815","12,767,118","12,776,309","12,788,313","12,784,826","12,782,275","12,787,641","12,800,922","12,801,989"
46+
Rhode Island,"1,053,959","1,053,649","1,054,621","1,055,081","1,055,936","1,056,065","1,056,770","1,055,673","1,058,287","1,059,361"
47+
South Carolina,"4,635,649","4,671,994","4,717,354","4,764,080","4,823,617","4,891,938","4,957,968","5,021,268","5,084,156","5,148,714"
48+
South Dakota,"816,166","823,579","833,566","842,316","849,129","853,988","862,996","872,868","878,698","884,659"
49+
Tennessee,"6,355,311","6,399,291","6,453,898","6,494,340","6,541,223","6,591,170","6,646,010","6,708,799","6,771,631","6,829,174"
50+
Texas,"25,241,971","25,645,629","26,084,481","26,480,266","26,964,333","27,470,056","27,914,410","28,295,273","28,628,666","28,995,881"
51+
Utah,"2,775,332","2,814,384","2,853,375","2,897,640","2,936,879","2,981,835","3,041,868","3,101,042","3,153,550","3,205,958"
52+
Vermont,"625,879","627,049","626,090","626,210","625,214","625,216","623,657","624,344","624,358","623,989"
53+
Virginia,"8,023,699","8,101,155","8,185,080","8,252,427","8,310,993","8,361,808","8,410,106","8,463,587","8,501,286","8,535,519"
54+
Washington,"6,742,830","6,826,627","6,897,058","6,963,985","7,054,655","7,163,657","7,294,771","7,423,362","7,523,869","7,614,893"
55+
West Virginia,"1,854,239","1,856,301","1,856,872","1,853,914","1,849,489","1,842,050","1,831,023","1,817,004","1,804,291","1,792,147"
56+
Wisconsin,"5,690,475","5,705,288","5,719,960","5,736,754","5,751,525","5,760,940","5,772,628","5,790,186","5,807,406","5,822,434"
57+
Wyoming,"564,487","567,299","576,305","582,122","582,531","585,613","584,215","578,931","577,601","578,759"
58+
Puerto Rico,"3,721,525","3,678,732","3,634,488","3,593,077","3,534,874","3,473,232","3,406,672","3,325,286","3,193,354","3,193,694"

‎tests/options/series/test_area.py‎

Lines changed: 31 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -2733,6 +2733,37 @@ def test_LineSeries_from_js_literal(input_files, filename, as_file, error):
27332733
Class_from_js_literal(cls5, input_files, filename, as_file, error)
27342734

27352735

2736+
@pytest.mark.parametrize('filename, property_map, error', [
2737+
('test-data-files/nst-est2019-01.csv', {}, ValueError),
2738+
('test-data-files/nst-est2019-01.csv',
2739+
{
2740+
'name': 'Geographic Area',
2741+
'x': 'Geographic Area',
2742+
'y': '2010'
2743+
},
2744+
None),
2745+
2746+
])
2747+
def test_LineSeries_from_pandas(input_files, filename, property_map, error):
2748+
import pandas
2749+
2750+
input_file = check_input_file(input_files, filename)
2751+
df = pandas.read_csv(input_file, header = 0, thousands = ',')
2752+
print(df.dtypes)
2753+
2754+
if not error:
2755+
result = cls5.from_pandas(df, property_map = property_map)
2756+
assert result is not None
2757+
assert isinstance(result, cls5)
2758+
assert result.data is not None
2759+
assert len(result.data) == len(df)
2760+
for item in result.data:
2761+
for key in property_map:
2762+
assert getattr(item, key, None) is not None
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else:
2764+
with pytest.raises(error):
2765+
result = cls5.from_pandas(df, property_map = property_map)
2766+
27362767
#### NEXT CLASS
27372768

27382769
@pytest.mark.parametrize('kwargs, error', STANDARD_PARAMS)

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