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kandi X-RAY | Data_Analysis Summary
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Trending Discussions on Data_Analysis
QUESTION
My code gets the job done but it is ugly, too long and clumsy. I have to work through several thousand files which fall into 4 groups and I only want one specific type
I want: '.docx'
I do not want: '.pdf', 'SS.docx', or 'ss.docx'
I tried several if not
but they did not really work. In the end I built lists of all file types and the anti-join them to the complete list one after another so that only the files I am interested remain.
Question:
is it possible to simplify my if elif block? Could this be done with less lines to directly get to only the files I need?
is it possible to pack the df generation into a loop instead of having to do it manually for each?
...ANSWER
Answered 2021-Mar-15 at 21:37Since you:
- Only want '.docx' (i.e. as determined by suffix)
- Do not want: '.pdf', 'SS.docx', or 'ss.docx' (i.e. fies with these endings)
This could be done more simply as follows.
Code--Option 1 using str endswith
QUESTION
CSS overflow:scroll;
property doesn't provide large scrolling depth. Unable to see the hidden data as scrollbar doesn't scroll enough.
My github link for the code is below. https://github.com/krishnasai3cks/portfolio
...ANSWER
Answered 2021-Jan-13 at 07:36Removing the display: flex
property from this class will fix it.
QUESTION
I want to run the following RandomizedSearch
:
ANSWER
Answered 2020-Nov-18 at 21:17I don't see an alternative to dropping RandomizedSearchCV
. Internally RandomSearchCV
calls sample_without_replacement
to sample from your feature space. When your feature space is larger than C's long
size, scikit-learn's sample_without_replacement
simply breaks down.
Luckily, random search kind of sucks anyway. Check out optuna
as an alternative. It is way smarter about where in your feature space to spend time evaluating (paying more attention to high-performing areas), and does not require you to limit your feature space precision beforehand (that is, you can omit the step size). More generally, check out the field of AutoML.
If you insist on random search however, you'll have to find another implementation. Actually, optuna
also supports a random sampler.
QUESTION
I am generating a bar chart from a dataframe, I want to remove the Y axis labels and display them above the bars. How can I achieve this?
This is my code so far:
ANSWER
Answered 2020-Jul-26 at 14:04using ax.patches
you can achieve it.
This will do:
QUESTION
org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.UnsupportedOperationException: Parquet does not support timestamp. See HIVE-6384;
Getting above error while executing following code in Azure Databricks.
...ANSWER
Answered 2020-Jun-21 at 13:39As per Hive-6384 Jira, Starting from Hive-1.2 you can use Timestamp,date
types in parquet tables.
Workarounds for Hive < 1.2 version:
1. Using String type:
QUESTION
ANSWER
Answered 2020-Jun-11 at 07:51Try the following (documentation is inside the code):
QUESTION
I tried to use thread to get better run-time result for some reasons the error
Missing 1 required positional argument: year is keeping popping on the screen
here is the function:
...ANSWER
Answered 2020-Apr-28 at 06:15Not really sure how your whole construct looks like, but the following should work...
QUESTION
I have this code:
...ANSWER
Answered 2020-Mar-20 at 00:58I believe you can accomplish what you want using GridSpec. The following code should produce what you want using simulated data:
QUESTION
Am trying to extract values from a pandas Dataframe which are split by an ID. However when I feed the apply groupby, it wont let me provide an axis argument to apply the function row wise
...ANSWER
Answered 2020-Mar-05 at 15:15I had a similar error. I found that the apply function of a GroupBy
object does not behave the same as the apply function of a Pandas DataFrame
. More information on the apply function of the GroupBy object can be found here.
The function you provide in your apply
function should get dataframe
as an argument. It also returns a dataframe
. The function thus modifies a dataframe
whereas the function you provided modifies a row.
It gives the error () got an unexpected keyword argument 'axis'
as the apply function here only accepts a function which modifies a dataframe and args kwargs which are fed to your function.
It tries to feed your lambda function the axis parameter (which it thinks is an argument for your function) and since your lambda function does not demand this parameter, it displays this error.
The solution for your end would be to change the lambda function to a correct function as described above.
QUESTION
In Google Colab, I mounted google drive:
...ANSWER
Answered 2019-Oct-07 at 02:54Assignin path = ...
doesn't change the current working directory. Instead, use the absolute path as suggested by Michael, or change the working directory using:
%cd /content/gdrive/My Drive
You can observe the current working directory using %pwd
and the files in the current directory using %ls
.
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You can use Data_Analysis like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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