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Google Datalab和Python问题

[英]Google Datalab and Python Issue

I have a python script that runs perfectly in my IDE on my local machine, but when I run it on Google Datalab, it throws this error: 我有一个可以在本地计算机上的IDE中完美运行的python脚本,但是当我在Google Datalab上运行它时,它将引发以下错误:

ValueError: could not convert string to float: '80,354' ValueError:无法将字符串转换为浮点型:'80,354'

The code is simple, and the graph prints in my Pycharm IDE, but not on GoogleDatalab. 代码很简单,图形可以在我的Pycharm IDE中打印,而不能在GoogleDatalab上打印。

plt.plot(new_df['Volume']) plt.show() plt.plot(new_df ['Volume'])plt.show()

The error is related to the last line in the data. 错误与数据的最后一行有关。 I'm using the date as an index. 我使用日期作为索引。 Here's what the data looks like? 数据如下所示? Is there a slash missing somehwere? 是否有斜线缺少? What am I doing wrong or missing? 我在做什么错还是想念?

' Micro Market Volume\\nMonth/Year \\n2014-01-01 DALLAS-FT WORTH 63,974\\n2014-02-01 DALLAS-FT WORTH 68,482\\n2014-03-01 DALLAS-FT WORTH 85,866\\n2014-04-01 DALLAS-FT WORTH 79,735\\n2014-05-01 DALLAS-FT WORTH 75,339\\n2014-06-01 DALLAS-FT WORTH 71,739\\n2014-07-01 DALLAS-FT WORTH 85,893\\n2014-08-01 DALLAS-FT WORTH 83,694\\n2014-09-01 DALLAS-FT WORTH 87,567\\n2014-10-01 DALLAS-FT WORTH 87,389\\n2014-11-01 DALLAS-FT WORTH 68,340\\n2014-12-01 DALLAS-FT WORTH 74,805\\n2015-01-01 DALLAS-FT WORTH 68,568\\n2015-02-01 DALLAS-FT WORTH 61,924\\n2015-03-01 DALLAS-FT WORTH 56,885\\n2015-04-01 DALLAS-FT WORTH 68,101\\n2015-05-01 DALLAS-FT WORTH 52,806\\n2015-06-01 DALLAS-FT WORTH 79,918\\n2015-07-01 DALLAS-FT WORTH 92,134\\n2015-08-01 DALLAS-FT WORTH 88,047\\n2015-09-01 DALLAS-FT WORTH 91,377\\n2015-10-01 DALLAS-FT WORTH 91,307\\n2015-11-01 DALLAS-FT WORTH 65,415\\n2015-12-01 DALLAS-FT WORTH 81,456\\n2016-01-01 DALLAS-FT WORTH 82,820\\n2016-02-01 DALLAS-FT WORTH 91,688\\n2016-03-01 DALLAS-FT WORTH 81,495\\n2016-04-01 DALLAS-F '微型市场交易量\\ n月/年\\ n2014-01-01 DALLAS-FT价值63,974 \\ n2014-02-01 DALLAS-FT价值68,482 \\ n2014-03-01 DALLAS-FT价值85,866 \\ n2014-04-01 DALLAS-FT价值79,735 \\ n2014-05-01 DALLAS-FT价值75,339 \\ n2014-06-01 DALLAS-FT价值71,739 \\ n2014-07-01 DALLAS-FT价值85,893 \\ n2014-08-01 DALLAS-FT价值83,694 \\ n2014-09 -01 DALLAS-FT价值87,567 \\ n2014-10-01 DALLAS-FT价值87,389 \\ n2014-11-01 DALLAS-FT价值68,340 \\ n2014-12-01 DALLAS-FT价值74,805 \\ n2015-01-01 DALLAS-FT价值68,568 \\ n2015-02-01 DALLAS-FT价值61,924 \\ n2015-03-01 DALLAS-FT价值56,885 \\ n2015-04-01 DALLAS-FT价值68,101 \\ n2015-05-01 DALLAS-FT价值52,806 \\ n2015-06- 01 DALLAS-FT价值79,918 \\ n2015-07-01 DALLAS-FT价值92,134 \\ n2015-08-01 DALLAS-FT价值88,047 \\ n2015-09-01 DALLAS-FT价值91,377 \\ n2015-10-01 DALLAS-FT价值91,307 \\ n2015-11-01 DALLAS-FT价值65,415 \\ n2015-12-01 DALLAS-FT价值81,456 \\ n2016-01-01 DALLAS-FT价值82,820 \\ n2016-02-01 DALLAS-FT价值91,688 \\ n2016-03-01 DALLAS-FT价值81,495 \\ n2016-04-01 DALLAS-F T WORTH 87,872\\n2016-05-01 DALLAS-FT WORTH 82,031\\n2016-06-01 DALLAS-FT WORTH 100,783\\n2016-07-01 DALLAS-FT WORTH 99,285\\n2016-08-01 DALLAS-FT WORTH 99,179\\n2016-09-01 DALLAS-FT WORTH 93,939\\n2016-10-01 DALLAS-FT WORTH 99,663\\n2016-11-01 DALLAS-FT WORTH 86,751\\n2016-12-01 DALLAS-FT WORTH 84,551\\n2017-01-01 DALLAS-FT WORTH 81,890\\n2017-02-01 DALLAS-FT WORTH 90,212\\n2017-03-01 DALLAS-FT WORTH 97,798\\n2017-04-01 DALLAS-FT WORTH 89,338\\n2017-05-01 DALLAS-FT WORTH 96,891\\n2017-06-01 DALLAS-FT WORTH 86,613\\n2017-07-01 DALLAS-FT WORTH 80,354' T价值87,872 \\ n2016-05-01 DALLAS-FT价值82,031 \\ n2016-06-01 DALLAS-FT价值100,783 \\ n2016-07-01 DALLAS-FT价值99,285 \\ n2016-08-01 DALLAS-FT价值99,179 \\ n2016- 09-01 DALLAS-FT价值93,939 \\ n2016-10-01 DALLAS-FT价值99,663 \\ n2016-11-01 DALLAS-FT价值86,751 \\ n2016-12-01 DALLAS-FT价值84,551 \\ n2017-01-01 DALLAS-FT价值81,890 \\ n2017-02-01 DALLAS-FT价值90,212 \\ n2017-03-01 DALLAS-FT价值97,798 \\ n2017-04-01 DALLAS-FT价值89,338 \\ n2017-05-01 DALLAS-FT价值96,891 \\ n2017-06 -01 DALLAS-FT值86,613 \\ n2017-07-01 DALLAS-FT值80,354'

I was loading the data inappropriately. 我加载数据不当。 I was using pandas load_csv on my local machine, and BytesIO on in Datalab. 我在本地计算机上使用pandas load_csv,在Datalab中使用BytesIO。 The comma in the numberical value was throwing off the import of the data. 数字值中的逗号使数据无法导入。 I had to say that the delimiter is a "," and the thousand separator is also a "," 我不得不说定界符是“,”而千位分隔符也是“,”

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