dataset | Shim for DOM dataset
kandi X-RAY | dataset Summary
kandi X-RAY | dataset Summary
Shim for DOM dataset
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Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of dataset
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dataset Examples and Code Snippets
def _from_dataset_id(processing_mode,
service,
dataset_id,
element_spec,
job_name=None,
consumer_index=None,
num_consumers=N
def bucket_by_sequence_length(element_length_func,
bucket_boundaries,
bucket_batch_sizes,
padded_shapes=None,
padding_values=None,
def get_single_element(dataset):
"""Returns the single element of the `dataset` as a nested structure of tensors.
The function enables you to use a `tf.data.Dataset` in a stateless
"tensor-in tensor-out" expression, without creating an iterato
Community Discussions
Trending Discussions on dataset
QUESTION
I am running the following in my React app and when I open the console in Chrome, it is printing the response.data[0] twice in the console. What is causing this?
...ANSWER
Answered 2021-Jun-16 at 02:48You have included fetching function in the component as it is, so it fires every time component being rendered. You better to include fetching data in useEffect hook just like this:
QUESTION
I have a grib file containing monthly precipitation and temperature from 1989 to 2018 (extracted from ERA5-Land).
I need to have those data in a dataset format with 6 column : longitude, latitude, ID of the cell/point in the grib file, date, temperature and precipitation.
I first imported the file using cfgrib. Here is what contains the xdata list after importation:
...ANSWER
Answered 2021-Jun-16 at 02:36Here is the answer after a bit of trial and error (only putting the result for tp variable but it's similar for t2m)
QUESTION
I have a dynamic query that adds WHERE clauses according to the parameters received:
...ANSWER
Answered 2021-Jun-15 at 23:39I found the answer with the following lines of code:
QUESTION
I have a dataset with many columns and I'd like to locate the columns that have fewer than n unique responses and change just those columns into factors.
Here is one way I was able to do that:
...ANSWER
Answered 2021-Jun-15 at 20:29Here is a way using tidyverse
.
We can make use of where
within across
to select the columns with logical short-circuit expression where we check
- the columns are
numeric
- (is.numeric
) - if the 1 is TRUE, check whether number of distinct elements less than the user defined n
- if 2 is TRUE, then check
all
theunique
elements in the column are 0 and 1 - loop over those selected column and convert to
factor
class
QUESTION
How do you calculate the model accuracy in RStudio for logistic regression. The dataset is from Kaggle.
...ANSWER
Answered 2021-Jun-15 at 21:39use the package ML metrics
QUESTION
I have this code which prints multiple tables
...ANSWER
Answered 2021-Jun-15 at 20:59So, this is a good opportunity to use purrr::map
. You are half way there by applying code to one dataframe.
You can take the code that you have written above and put it into a function.
QUESTION
I have a dataset with various "chunks" of columns with different prefixes, but the same suffix:
ID A034 B034 C034 D034 A099 B099 A123 B123 ... 1 NA 1 NA NA NA 3 1 NA ... 2 2 NA NA NA 2 NA NA 2 ... 3 NA NA 2 NA NA 2 1 NA ...The number of columns within each "chunk" also varies. Is there any way (other than manually, which is what I have been painstakingly doing with coalesce(!!! select(., contains("XXX")))
) to automatically coalesce by chunk based on the shared suffix? That is, the result should resemble
I'm not sure how to begin doing something like this, so any suggestions would be very helpful.
...ANSWER
Answered 2021-Jun-15 at 20:10We reshape the data into 'long' format with pivot_longer
, then we group by 'ID' and loop across
the other columns, apply the na.omit
to remove the NA elements (we assume that there is only one non-NA per each column by group)
QUESTION
I am relatively new in dealing with txt and json datasets. I have a dialogue dataset in a txt file and i want to convert it into a csv file with each new line converted into a column. and when the next dialog starts (next paragraph), it starts with a new row. so i get data in format of
...ANSWER
Answered 2021-Jun-15 at 19:08A CSV file is a list of strings separated by commas, with newlines (\n
) separating the rows.
Due to this simplistic layout, it is often not suitable for containing strings that may contain commas within them, for instance dialogue.
That being said, with your input file, it is possible to use regex to replace any single newlines with a comma, which effectively does the "each new line converted into a column, each new paragraph a new row" requirement.
QUESTION
I have a list (dput() below) that has 4 datasets.I also have a variable called 'u' with 4 characters. I have made a video here which explains what I want and a spreadsheet is here.
The spreadsheet is not exactly how my data looks like but i am using it just as an example. My original list has 4 datasets but the spreadsheet has 3 datasets.
Essentially i have some characters(A,B,C,D) and i want to find the proportions of times each character occurs in each column of 3 groups of datasets.(Check video, its hard to explain by typing it out)
...ANSWER
Answered 2021-Jun-09 at 19:00We can loop over the list
'l' with lapply
, then get the table
for each of the columns by looping over the columns with sapply
after converting the column to factor
with levels
specified as 'u', get the proportions
, t
ranspose, convert to data.frame
(as.data.frame
), split by row (asplit
- MARGIN = 1), then use transpose
from purrr
to change the structure so that each column from all the list
elements will be blocked as a single unit, bind them with bind_rows
QUESTION
I have a Graph loaded in pandas and I want to check if my graph has nodes with reciprocity. My dataset looks like this:
id from to 0 s01 s03 1 s02 s01 2 s03 s01The desired output of my code is the reciprocal nodes: (s01, s03)
I found a solution transforming my dataframe into tuples and comparing each combination of my nodes, but I'm sure this solution is far from ideal. Following is my code:
...ANSWER
Answered 2021-Jun-15 at 18:22You can merge the DataFrame with itself after swapping the from and to columns in the right DataFrame. Then sort
the merged result and drop duplicates to get the unique pairs of reciprocal nodes.
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