2020-1 | Materiales y recursos para alumnos que cursan en la
kandi X-RAY | 2020-1 Summary
kandi X-RAY | 2020-1 Summary
Materiales y recursos para alumnos que cursan en la Facultad de Ingeniería en materias que imparto durante el semestre 2020-1
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QUESTION
DataFrame :df
...ANSWER
Answered 2021-Jun-15 at 12:41Use custom lambda function in list comprehension:
QUESTION
I have a column that gives the date (its type is str) and another column that gives a first name, I would like all the names that are in 2020 have "_2020" at the end of their first name, and same thing for 2021, and its pandas DataFrame.
As I have thousands of rows, I need a loop that automates the task.
it would be like going from this:
Time Name 2020-12-26 John 2020-05-06 Jack 2021-03-06 SteveTo That:
Time Name 2020-12-26 John_2020 2020-05-06 Jack_2020 2021-03-06 Steve_2021 ...ANSWER
Answered 2021-Jun-15 at 12:20try:
QUESTION
Tell me please, we have a date, for example 2020-06-15. I need to add one month one year ahead, and also change the date to the last day of the month. That is, in the result it should turn out:
- 2020-06-15 (first date)
- 2020-07-31 (31 days in July)
- 2020-08-31 (31 days in August)
- 2020-09-30 (30 days in September)
- 2020-10-31 (31 days in October)
and so on until July 22 year.
I try like this:
...ANSWER
Answered 2021-Jun-15 at 07:34You need to get the values in $month
and $year
after changing the date $date->modify("+$i month");
, not before :
QUESTION
I have 2 JSONs that I get from separate API calls.
Here is first one:
...ANSWER
Answered 2021-Jun-15 at 09:17try this code, if you project allows you to create classes for the JSON you receives.
first created these classes
QUESTION
I have a such a table in my db
id amount created_at 1 30 2020-02-02 22:14:56 2 20 2020-05-29 22:14:56 3 20 2020-08-29 22:14:56 4 40 2020-12-29 22:14:56My result should like this
amount half_of_year 25 1 (1st half) 30 2 (2nd half)I need calculate average amount according to first and second half of the year and show them separately
I have no idea how to select and group by date
...ANSWER
Answered 2021-Jun-15 at 06:50SELECT YEAR(date) `year`,
(MONTH(date) > 6) + 1 `half`,
AVG(amount) avg_amount
FROM source_table
GROUP BY 1, 2
QUESTION
I obtained the information from Twitter and would like to sort the dates. However, some of the dates are incorrectly sorted, switching from date to month and vice versa.Is there something wrong with the code or the original data? My original data looked fine, though. Can anyone help?
Raw data
my code
...ANSWER
Answered 2021-Jun-15 at 05:29Here seems day is not first, but month, so remove dayfirst=True
:
QUESTION
import yfinance as yf
msft = yf.Ticker('MSFT')
data = msft.history(period='6mo')
import mplfinance as mpf
data['30 Day MA'] = data['Close'].rolling(window=20).mean()
data['30 Day STD'] = data['Close'].rolling(window=20).std()
data['Upper Band'] = data['30 Day MA'] + (data['30 Day STD'] * 2)
data['Lower Band'] = data['30 Day MA'] - (data['30 Day STD'] * 2)
apdict = (
mpf.make_addplot(data['Upper Band'])
, mpf.make_addplot(data['Lower Band'])
)
mpf.plot(data, volume=True, addplot=apdict)
...ANSWER
Answered 2021-Jun-15 at 01:49- As per Adding plots to the basic mplfinance plot(), section Plotting multiple additional data sets
- Aside from the example below, for two columns from a dataframe, the documentation shows a number of ways to configure an appropriate object for the
addplot
parameter. apdict = [mpf.make_addplot(data['Upper Band']), mpf.make_addplot(data['Lower Band'])]
works as well. Note it's alist
, not atuple
.
- Aside from the example below, for two columns from a dataframe, the documentation shows a number of ways to configure an appropriate object for the
- mplfinance/examples
QUESTION
transform file/directory structure into 'tree' in vue json
I have an array of objects that looks like this:
...ANSWER
Answered 2021-Jun-11 at 09:55EDIT
Here is the full implementation, based upon my initial answer. I changed the forEach() into map() as it is more suitable in this case.
QUESTION
I have the following data frame called "new_df":
...ANSWER
Answered 2021-May-18 at 21:08That's probably due to the wrong data type. You can try this.
QUESTION
There is a Java 11 (SpringBoot 2.5.1) application with simple workflow:
- Upload archives (as multipart files with size 50-100 Mb each)
- Unpack them in memory
- Send each unpacked file as a message to a queue via JMS
When I run the app locally java -jar app.jar
its memory usage (in VisualVM) looks like a saw: high peaks (~ 400 Mb) over a stable baseline (~ 100 Mb).
When I run the same app in a Docker container memory consumption grows up to 700 Mb and higher until an OutOfMemoryError. It appears that GC does not work at all. Even when memory options are present (java -Xms400m -Xmx400m -jar app.jar
) the container seems to completely ignore them still consuming much more memory.
So the behavior in the container and in OS are dramatically different.
I tried this Docker image in DockerDesktop Windows 10
and in OpenShift 4.6
and got two similar pictures for the memory usage.
Dockerfile
...ANSWER
Answered 2021-Jun-13 at 03:31In Java 11, you can find out the flags that have been passed to the JVM and the "ergonomic" ones that have been set by the JVM by adding -XX:+PrintCommandLineFlags
to the JVM options.
That should tell you if the container you are using is overriding the flags you have given.
Having said that, its is (IMO) unlikely that the container is what is overriding the parameters.
It is not unusual for a JVM to use more memory that the -Xmx
option says. The explanation is that that option only controls the size of the Java heap. A JVM consumes a lot of memory that is not part of the Java heap; e.g. the executable and native libraries, the native heap, metaspace, off-heap memory allocations, stack frames, mapped files, and so on. Depending on your application, this could easily exceed 300MB.
Secondly, OOMEs are not necessarily caused by running out of heap space. Check what the "reason" string says.
Finally, this could be a difference in your app's memory utilization in a containerized environment versus when you run it locally.
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