bef | Bef is a responsive jekyll theme https | Theme library

by artemsheludko CSS Version: Current License: GPL-3.0

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kandi X-RAY | bef Summary

bef is a CSS library typically used in User Interface, Theme, Jekyll applications. bef has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Bef - Blog Enjoy Freedom is a responsive jekyll theme which created to be simple and freedom.

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bef has a low active ecosystem.

It has 145 star(s) with 289 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 0 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of bef is current.

Quality

bef has 0 bugs and 0 code smells.

Security

bef has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

bef code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

bef is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

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bef releases are not available. You will need to build from source code and install.

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bef Key Features

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bef Examples and Code Snippets

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Community Discussions

Trending Discussions on bef

ElementTree not finding present tags

Extracting specific data from multiple text files and writing them into columns in csv

adjusting horizontal bar chart matplotlib to accommodate the bars

Get items from list if the item contains any of the strings in another list (Python)

How to Return rows of XML Nested Nodes as a string separated by a Comma (,) character

How to run a for loop through two different variable types in Python?

AspectJ inside a testing framework

How do I convert currencies to dollars in a dataframe

How to make pandas to use nulls for int64 column when reading CSV file

Split an array of objects in to two, based on a value within the object

QUESTION

ElementTree not finding present tags

Asked 2022-Feb-23 at 15:19

Here's how I parse the xml response from this url

...

ANSWER

Answered 2022-Feb-23 at 15:19

Unfortunately, you have to deal with the namespace in the file. So try it this way:

Source https://stackoverflow.com/questions/71239102

QUESTION

Extracting specific data from multiple text files and writing them into columns in csv

Asked 2022-Jan-30 at 21:15

I'm trying to write a code that will search for specific data from multiple report files, and write them into columns in a single csv.

The report file lines i'm looking for aren't always on the same line, so i'm looking for the data associated on the lines below:

Estimate file: pog_example.bef

Estimate ID: o1_p1

61078 (100.0%) estimated.

And I want to write the data from each text file into columns in a csv as below:

example.bef, o1_p1, 61078 (100.0%) estimated

So far I have this script which will list out the first of my criteria, but I can't figure out how to loop it through to find my second and third lines to populate the second and third columns

...

ANSWER

Answered 2022-Jan-30 at 00:20

I think I see what you're trying to do, but I'm not sure.

I think your BEF file might look something like this:

Source https://stackoverflow.com/questions/70909920

QUESTION

adjusting horizontal bar chart matplotlib to accommodate the bars

Asked 2022-Jan-17 at 08:36

I am doing a horizontal bar chart but struggling with adjusting ylim, or maybe another parameter to make my labels clearer and make all the labels fit the y axis . I played around with ylim and the text size can be bigger or smaller but the bars do not fit the y axis. Any idea about the right approach?

My code:

...

ANSWER

Answered 2022-Jan-17 at 08:36

To make the labels fit, you need to set a smaller fontsize, or use a larger figsize. Changing the ylim will either just show a subset of the bars (in case ylim is set too narrow), or will show more whitespace (when ylim is larger).

The biggest problem in the code is width being too large. Twice the width needs to fit over a distance of 1.0 (the ticks are placed via ind, which is an array 0,1,2,...). As matplotlib calls the thickness of a horizontal bar plot "height", this name is used in the example code below. Using align='edge' lets you position the bars directly (align='center' will move them half their "height").

Pandas has simple functions to sort dataframes according to one or more rows.

Code to illustrate the ideas:

Source https://stackoverflow.com/questions/70736418

QUESTION

Get items from list if the item contains any of the strings in another list (Python)

Asked 2021-Dec-21 at 16:43

I have a list that looks like:

...

ANSWER

Answered 2021-Dec-20 at 23:35

The argument to any() has to be a sequence of booleans. You just have a single boolean, and it's not the condition you want.

You want to test whether each of ab and ac is in the string, not a tuple or list of them.

Source https://stackoverflow.com/questions/70429125

QUESTION

How to Return rows of XML Nested Nodes as a string separated by a Comma (,) character

Asked 2021-May-10 at 11:53

Need help to with a query below to return rows of following XML nested nodes. Some of column's data require to return multiple values (as exist in XML script) with comma separated e.g. nodes 'BillType', 'BillNumber', 'CONTAINER_NUMBER' or 'CONTAINER_STATUS' etc..

Thanks in Advance.

XML...

...

ANSWER

Answered 2021-May-10 at 11:53

Aggregate Bills info as CSV of type(identifier)

Source https://stackoverflow.com/questions/67467456

QUESTION

How to run a for loop through two different variable types in Python?

Asked 2021-May-04 at 19:08

I would like to loop through the axes (0 to 5 & 0 to 1), as well as loop through the columns of my series table (Pandas).

My idea was to do something along the lines of the following:

...

ANSWER

Answered 2021-May-04 at 19:08

You can zip the dataframe's columns and the flattened axis together and then run a loop:

Source https://stackoverflow.com/questions/67390682

QUESTION

AspectJ inside a testing framework

Asked 2021-Apr-13 at 06:54

I'm trying to apply a cross cutting concern which is logging with AspectJ and a test framework called Katalon which uses Groovy and Java. I found that the best weaving type appropriate here is load-time weaving which requires a META-INF folder and an Aop.xml. I tried to put my aop.xml in multiple places but I think aspectj is unable to find it. This is the structure of my project:

Here is my aop.xml file content:

...

ANSWER

Answered 2021-Apr-13 at 06:54

My first guess, not having seen your real project, is that you should move the weaver options out of the aspect declaration section like this:

Source https://stackoverflow.com/questions/67051936

QUESTION

How do I convert currencies to dollars in a dataframe

Asked 2021-Mar-19 at 20:52

array(['DEM 6000000', '$ 1500000', '$ 60000', '$ 1499000', '$ 3977000',
       '$ 1900000', '$ 2777000', '$ 2280000', '$ 2600000', '$ 839727',
       '$ 950000', '$ 48000000', '$ 2100000', '$ 3000000', '$ 1400000',
       '$ 2900000', '$ 250000', '$ 2723903', '$ 2540800', '$ 1650000',
       '$ 30000', '$ 4000000', '$ 2000000', '$ 175000', '$ 1000000',
       'JPY 125000000', '$ 5019770', 'FRF 17500000', '$ 5400000',
       '$ 829000', '$ 2479000', '$ 15000000', '$ 6000000', '$ 180000',
       '$ 806947', '$ 12000000', '$ 5000000', '$ 160000', '$ 1100000',
       '$ 2200000', '$ 44000000', '$ 1800000', '$ 9400000', '$ 120000',
       '$ 560000', '$ 17000000', '$ 200000', '$ 800000', '$ 11000000',
       '$ 3800000', '$ 600000', '$ 8200000', '$ 9000000', '$ 1200000',
       '$ 7500000', '$ 1600000', '$ 9500000', '$ 5500000', '$ 14100000',
       '$ 114000', '$ 5800000', '$ 941000', '$ 360000', '$ 25000000',
       '$ 3600000', '$ 7000000', '$ 20000000', '$ 2500000', '$ 7700000',
       '$ 6244087', '$ 10000000', '$ 750000', '$ 3500000', '$ 777000',
       '$ 7200000', '$ 1300000', 'AUD 800000', '$ 725000', '$ 1585000',
       '$ 1700000', 'RUR 1000000', '$ 500000', '$ 1250000', '$ 810000',
       '$ 13000000', '$ 6500000', 'GBP 229575', 'GBP 1500000', '$ 300000',
       '$ 14000000', '$ 2800000', '$ 4340000', 'AUD 440000', '$ 8500000',
       'GBP 575000', '$ 24000000', '$ 3700000', '$ 960000', '$ 4400000',
       '$ 3200000', '$ 4015000', '$ 7840000', 'AUD 810000', '$ 4300000',
       '$ 6800000', '$ 7920000', '$ 325000', '$ 2700000', '$ 18000000',
       '$ 55000000', '$ 35000000', '$ 4700000', '$ 31500000', '$ 5450000',
       '$ 2300000', '$ 12164000', '$ 8000000', 'GBP 10000000',
       'CAD 1600000', '$ 16000000', '$ 34000000', 'JPY 5000000000',
       '$ 4800000', '$ 4500000', '$ 27000000', '$ 550000', 'CAD 1500000',
       'CAD 4100000', '$ 19000000', '$ 5100000', '$ 54000000',
       'DEM 32000000', '$ 400000', '$ 28000000', 'AUD 2600000',
       '$ 12500000', 'CAD 6500000', '$ 9300000', 'CAD 2300000',
       '$ 22000000', '$ 32000000', '$ 50000000', '$ 11300000',
       '$ 10500000', '$ 350000', '$ 13200000', '$ 26000000',
       'CAD 3500000', '$ 10700000', '$ 11200000', '$ 21000000',
       '$ 4520000', '$ 5600000', '$ 9700000', '$ 3300000', '$ 20500000',
       '$ 47000000', '$ 36000000', '$ 27500000', '$ 32500000', '$ 700000',
       '$ 6200000', '$ 39000000', '$ 14500000', '$ 5952000', '$ 58000000',
       '$ 40000000', '$ 4600000', '$ 30000000', '$ 14400000',
       '$ 15100000', '$ 2550000', 'GBP 3000000', 'GBP 1162000',
       '$ 1065000', '$ 90000', '$ 6400000', '$ 17500000', '$ 24500000',
       '$ 31000000', '$ 6900000', '$ 7600000', '$ 11500000', '$ 900000',
       '$ 17900000', '$ 2400000', 'FRF 17000000', '$ 8800000',
       '$ 18500000', '$ 8700000', 'GBP 450000', '$ 13800000',
       'CAD 1800000', '$ 37000000', '$ 3401376', 'GBP 650000',
       'ITL 30000000000', '$ 8300000', '$ 29000000', 'CAD 2500000',
       '$ 100000', '$ 23000000', 'GBP 23000000', 'GBP 1577000',
       '$ 22700000', '$ 3520000', 'DEM 800000', 'FRF 80000000',
       'GBP 1800000', '$ 63000000', '$ 70000000', '$ 46630000',
       '$ 22500000', '$ 10400000', '$ 16400000', 'JPY 800000000',
       '$ 27800000', '$ 33000000', '$ 38000000', '$ 5200000',
       '$ 60000000', 'CAD 22000000', '$ 111000', '$ 5300000', '$ 230000',
       '$ 4200000', 'FRF 50000000', '$ 42000000', '$ 13500000',
       '$ 65000000', 'FRF 24000000', '$ 6788000', 'DKK 28000000',
       '$ 17010000', '$ 23000', '$ 102000000', '$ 16500000', '$ 49000000',
       '$ 80000000', 'BEF 1000000', 'GBP 2300000', '$ 41000000',
       '$ 11700000', '$ 22769', '$ 7000', '$ 45000000', 'AUD 3000000',
       '$ 43000000', '$ 57000000', '$ 14600000', '$ 85000000',
       '$ 62000000', '$ 27000', 'HKD 40000000', 'CAD 2000000',
       '$ 46000000', 'FRF 115000000', '$ 65897768', '$ 75000000',
       '$ 7400000', '$ 115000000', '$ 52000000', '$ 100000000',
       '$ 72000000', '$ 53000000', '$ 98000000', '$ 90000000',
       '$ 30250000', 'JPY 600000000', '$ 150000', '$ 29000001',
       '$ 175000000', '$ 4100000', '$ 25530000', '$ 21500000',
       'DKK 6000000', '$ 92000000', '$ 125000000', '$ 116000000',
       '$ 71500000', 'FRF 82000000', '$ 93000000', '$ 25000', '$ 740000',
       '$ 73000000', '$ 31190000', 'JPY 2400000000', 'AUD 16000000',
       '$ 68000000', '$ 160000000', '$ 105000000', 'CAD 5000000',
       '$ 200000000', '$ 110000000', 'GBP 3500000', '$ 140000000',
       '$ 51000000', '$ 120000000', '$ 130000000', 'GBP 960000',
       '$ 95000000', '$ 11350000', '$ 170000000', '$ 66000000',
       '$ 113000000', 'CAD 365000', '$ 82000000', 'DEM 15000000',
       '$ 127500000', 'DEM 3500000', '$ 76000000', '$ 94000000',
       '$ 34200000', '$ 135000000', 'GBP 2000000', '$ 84000000',
       '$ 139000000', 'SEK 9000000', '$ 6000', '$ 64000000', '$ 29750000',
       '$ 83000000', '$ 79000000', '$ 312000', 'EUR 7000000', '$ 40000',
       '$ 133000000', 'GBP 1900000', '$ 12800000', 'INR 1091250',
       '$ 123000000', '$ 103000000', '$ 137000000', 'EUR 2850000',
       'ESP 400000000', '$ 225000', 'DEM 8400000', 'GBP 2200000',
       'FRF 65000000', '$ 41300000', 'ESP 125000000', 'FRF 100000000',
       '$ 3400000', '$ 5250000', 'SEK 17000000', 'GBP 1365000',
       '$ 7300000', 'GBP 6000000', '$ 63600000', '$ 8600000',
       '$ 87000000', 'CAD 20000000', 'CAD 1000000', 'AUD 5000000',
       '$ 21150000', '$ 150000000', 'FRF 39000000', 'FRF 53000000',
       'FRF 25000000', 'FRF 95130000', '$ 17700000', '$ 142000000',
       '$ 15600000', '$ 107000000', 'FRF 10000000', '$ 7100000',
       'ATS 70000000', '$ 10000', 'GBP 1600000', 'EUR 40000000',
       '$ 42000', 'FRF 48000000', 'INR 7000000', 'FRF 29000000',
       '$ 59000000', 'FRF 30000000', 'EUR 4800000', '$ 15500000',
       '$ 10600000', 'DKK 86000000', 'FRF 49000000', 'NOK 15500000',
       '$ 56000000', 'EUR 5328737', 'FRF 103000000', '$ 19800000',
       '$ 11800000', 'EUR 15300000', 'FRF 18000000', 'EUR 2000000',
       'EUR 8000000', 'EUR 5300000', 'EUR 7032000', '$ 80000',
       'ESP 1200000', 'CAD 1960000', 'GBP 3500159', '$ 78000000',
       'THB 400000000', 'EUR 19000000', 'GBP 2500000', 'BRL 12000000',
       'FRF 85000000', 'INR 280000000', '$ 125000', '$ 12600000',
       '$ 825000', '$ 24000', 'GBP 1950000', '$ 5740000', 'EUR 900000',
       'EUR 15920000', 'EUR 2717930', 'GBP 75000', 'FIM 8000000',
       '$ 109000000', 'EUR 3300000', '$ 81000000', 'BRL 3300000',
       '$ 250050', 'EUR 5000000', 'GBP 7000000', '$ 35200000',
       'SGD 4500000', '$ 128000000', 'EUR 5000', 'CAD 3000000',
       'EUR 2200000', 'CAD 6000000', 'SEK 22000000', '$ 165000000',
       'EUR 59660000', 'AUD 1000', '$ 6428966', 'AUD 2000000',
       'EUR 2400000', 'AUD 1000000', 'DKK 50000000', '$ 14200000',
       '$ 9600000', '$ 56600000', '$ 86000000', '$ 850000', '$ 155000000',
       'JPY 2000000000', '$ 450000', '$ 270000000', '$ 37665000',
       'EUR 1100000', '$ 88000000', '$ 9750000', 'EUR 5250784',
       '$ 19250000', '$ 207000000', 'EUR 11700000', '$ 180000000',
       'GBP 4000000', '$ 20000', 'HUF 2500000000', '$ 185000000',
       '$ 50000', '$ 46000', 'EUR 10000000', '$ 215000', 'EUR 5500000',
       '$ 780000', 'BRL 8000000', 'HUF 100000000', 'EUR 2500000',
       '$ 33100000', '$ 210000000', 'MXN 25000000', 'GBP 1000000',
       'GBP 1700000', 'INR 100000000', 'AUD 15000000', '$ 225000000',
       'CNY 100000000', 'CNY 10000000', 'EUR 1601792', 'GBP 4500',
       '$ 82500000', '$ 475000', 'EUR 1000000', 'EUR 4750000',
       '$ 260000000', '$ 70000', '$ 185000', '$ 126000000', 'EUR 750000',
       '$ 650000', 'CZK 36000000', '$ 250000000', 'CAD 500000',
       'BRL 5200000', '$ 132000000', 'EUR 1790000', '$ 163000000',
       'HUF 500000000', '$ 19300000', 'EUR 21166000', '$ 258000000',
       'EUR 12000000', '$ 72500000', '$ 3750000', 'HKD 60000000',
       'GBP 695393', 'CHF 500000', 'EUR 2700000', 'AUD 11400000',
       'EUR 4500000', '$ 7900000', '$ 16800000', 'GBP 2800000',
       '$ 149000000', 'DKK 10000000', 'GBP 8000000', 'EUR 2000',
       'CNY 553632000', '$ 69000000', 'THB 200000000', 'EUR 600000',
       '$ 10200000', 'JPY 5000000', '$ 15000', 'GBP 9800000',
       'EUR 2150000', '$ 1234567', 'EUR 7450000', 'EUR 6000000',
       'EUR 14500000', '$ 169000', '$ 61000000', '$ 19400000',
       'EUR 3000000', 'GBP 26000000', 'GBP 14000', '$ 300000000',
       'EUR 25320000', 'INR 400000000', 'KRW 4200000000', '$ 35000',
       '$ 60795000', '$ 5000', 'EUR 1380000', 'CAD 750000', 'GBP 300000',
       '$ 67000000', 'SGD 200000', 'EUR 3400000', 'GBP 5000000',
       'EUR 14000000', 'AUD 2200000', 'GBP 3800000', 'KRW 12215500000',
       'EUR 1500000', 'CAD 11000000', 'EUR 15000000', 'GBP 1500',
       'EUR 1400000', '$ 3900000', 'GBP 500000', 'CAD 4000000',
       'EUR 12800000', 'INR 150000000', '$ 237000000', 'EUR 20000000',
       'GBP 25000000', 'CAD 12000000', 'THB 300000000', 'EUR 8400000',
       'EUR 4000000', 'GBP 13000000', 'HKD 35000000', 'EUR 16000000',
       'EUR 24000000', '$ 14700000', 'EUR 200000', 'EUR 4200000',
       '$ 190000000', '$ 37500000', 'EUR 1300000', 'NOK 22000000',
       'EUR 980000', 'EUR 1450000', '$ 220000000', 'JPY 300000000',
       'BRL 3000000', '$ 145000000', 'GBP 13500000', 'EUR 300000',
       'DKK 45000000', 'GBP 150000000', '$ 230000000', '$ 55000',
       'EUR 4773906', '$ 15700000', 'GBP 900000', '$ 117000000',
       'EUR 5700000', '$ 44500000', '$ 138000000', 'EUR 590000',
       'EUR 800000', 'EUR 6400000', '$ 9800000', 'GBP 150000',
       '$ 26350000', '$ 10800000', '$ 13000', 'AUD 6500000', '$ 23600000',
       '$ 25100000', 'INR 550000000', '$ 430000', 'INR 600000000',
       '$ 215000000', 'EUR 3600000', 'GBP 612650', 'AUD 3500000',
       'EUR 9200000', '$ 49900000', '$ 17000', '$ 19100000', 'EUR 500000',
       '$ 16700000', 'EUR 3900000', 'KRW 1300000000', '$ 144000000',
       'EUR 2300000', 'EUR 17000000', 'GBP 7500000', '$ 112000000',
       'EUR 11500000', 'GBP 20000000', '$ 195000000', 'EUR 12500000',
       'EUR 2100000', '$ 50200000', 'EUR 13000000', 'EUR 1948000',
       'EUR 4255932', 'EUR 240000', 'INR 102000000', '$ 209000000',
       'EUR 25000000', '$ 13300000', 'EUR 9000000', 'BRL 20000000',
       'AUD 25000000', '$ 38600000', 'EUR 8700000', 'EUR 7740000',
       'EUR 3850000', 'CAD 1100000', '$ 65000', 'CAD 600000', '$ 8900000',
       'EUR 11000000', 'KRW 30000000000', '$ 16600000', 'NOK 30300000',
       '$ 176000000', 'EUR 3700000', '$ 178000000', '$ 6600000',
       'EUR 9150000', 'NOK 17500000', '$ 12700000', 'GBP 6400000',
       'CZK 175000000', 'EUR 9500000', 'AUD 2500000', 'EUR 2472000',
       '$ 39200000', 'GBP 120000', '$ 930000', 'EUR 9700000', '$ 1009653',
       'NOK 19900000', '$ 19500000', '$ 25500000', '$ 81200000',
       '$ 6700000', '$ 3100000', '$ 40600000', '$ 16200000', '$ 7395080',
       '$ 9980000', 'EUR 9600000', 'PLN 34148170', 'EUR 5600000',
       'HKD 200000000', 'CLP 153000000', 'EUR 13500000', '$ 97600000',
       'EUR 3100000', '$ 335000', '$ 270000', 'GBP 4900000',
       'EUR 4300000', 'CNY 30000000', 'EUR 3200000', 'GBP 1300000',
       'EUR 15400000', 'EUR 8500000', 'SEK 63000000', '$ 1850000',
       '$ 58800000', 'EUR 850000', 'BRL 1860000', 'NZD 3500000',
       'NGN 1270000000', 'DKK 15500000', 'AUD 1300000', '$ 177200000',
       'ARS 2000000', '$ 14800000', '$ 74000000', '$ 937000',
       'EUR 103000', '$ 97000000', 'EUR 6500000', 'HUF 953000000',
       'MXN 12000000', '$ 420000', '$ 108000000', 'NOK 38500000',
       'EUR 5555559', 'CNY 150000000', 'GBP 316000', '$ 12000',
       '$ 245000000', '$ 50100000', '$ 129000000', 'EUR 6900000',
       '$ 10900000', '$ 99000000', 'GBP 8200000', 'ARS 3000000',
       '$ 317000000', '$ 275000000', 'EUR 1605000', 'EUR 4576591',
       '$ 127000000', 'EUR 10500000', 'EUR 1880000', 'HKD 15000000',
       'EUR 470000', 'NOK 35000000', 'HUF 700000000', 'AUD 17000000',
       'GBP 12000000', 'EUR 7700000', 'EUR 650000', 'EUR 1500',
       'EUR 2896000', 'EUR 12300000', '$ 9900000', '$ 217000000',
       '$ 111000000', '$ 12400000', 'GBP 700000', '$ 495000', 'CAD 60000',
       'AUD 3992880', 'CAD 13000000', 'EUR 4993020', 'BRL 4000000',
       'EUR 3800000', 'EUR 8555500', 'EUR 10300000', 'DKK 35500000',
       '$ 2480421', 'EUR 100000', 'EUR 1700000', 'AUD 1500000',
       'KRW 10000000000', '$ 321000000', '$ 356000000', 'GBP 5500000',
       'EUR 63000000', 'JPY 234000000', 'EUR 1350000', 'ILS 3850000',
       'EUR 1250000', 'CAD 61000000', 'GBP 400000', 'GBP 5400000',
       'EUR 4635000', 'CNY 200000', '$ 104000000', 'EUR 14582000',
       '$ 60720000', '$ 4900000', 'MXN 26040000', '$ 8620000',
       '$ 12620000', 'EUR 3500000', '$ 21400000', '$ 162000000',
       'EUR 1800000', '$ 6420000', 'BRL 2500000', 'EUR 1600000',
       'EUR 7870000', '$ 63300000', '$ 13600000', 'JPY 370000000',
       '$ 4250000', 'EUR 11110000', 'DOP 25185569', 'SEK 165000000',
       'EUR 1467000', 'EUR 76000', 'EUR 8900000', 'EUR 960000',
       '$ 183000000', 'ISK 250000000', 'NOK 47500000', 'BRL 500000',
       'NOK 52100000', 'EUR 600', '$ 11400000', 'EUR 5800000',
       'CNY 300000000', 'CAD 8000000', '$ 30100000', 'EUR 30690000',
       '$ 880000', '$ 84500000', 'EUR 514000', 'KRW 100000',
       'JPY 3000000', 'KRW 19000000000', 'EUR 2600000', '$ 29900000',
       '$ 11100000'], dtype=object)

...

ANSWER

Answered 2021-Mar-19 at 20:52

Try this:

Source https://stackoverflow.com/questions/66711357

QUESTION

How to make pandas to use nulls for int64 column when reading CSV file

Asked 2021-Mar-18 at 14:00

I'm trying to read an old DBase file exported to CSV and some columns are just empty. First I had a problem with converting integer columns to float but tanks to @Nathan's answer here Pandas read_csv dtype read all columns but few as string the problem was resolved. After I had the right column types - using code bellow:

...

ANSWER

Answered 2021-Mar-18 at 09:10

You have 2 ways to use NULL values (in database sense) in a Pandas column containing integer value.

the still official way: convert the column to float64 and use NaN for NULL values.

The nice thing is that np.nan support is good in most database adapters, so all NaN values should be automatically converted to NULL database values if you insert (or update) them in a database. The downside is that float64 cannot hold exactly integer values higher than 2**48 (IEEE 754 mantissa is only 48 bits).
the experimental way: use the new pd.Int64Dtype

This new type can hold any 64 bit integer value and a special pd.NA value. So it provides exactly what you want. The downside here is that the documentation explicitely says:

IntegerArray is currently experimental. Its API or implementation may change without warning.

Long story short, it may work or not for your use case (support in the database adapter) and you could have to adapt your code if something change in a later version.

Source https://stackoverflow.com/questions/66674683

QUESTION

Split an array of objects in to two, based on a value within the object

Asked 2021-Jan-28 at 22:47

I have been trying (and struggling) to figure out how I am able to split an array of objects, based on a key value pair

Long story short, I have a list of stations that a train is calling at, and need to separate the stations previous calling points, and the stations future calling points.

The data i'm working with looks like this:

...

ANSWER

Answered 2021-Jan-28 at 22:13

Use Array.findIndex() to find the index of separating item, and then use Array.slice() to get the array before, the item, and the array after.

Source https://stackoverflow.com/questions/65945891

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install bef

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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