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404 error for Google Tag Manager
You need to publish a version of your container. If it is not published, the request will return a 404 error. To publish your current workspace: Click Submit at the top right hand side of the screen. The Submit Changes screen will appear, with options to publish the container and save a version of yRead more
You need to publish a version of your container. If it is not published, the request will return a 404 error.
See lessCypress: Test if element does not exist
Well this seems to work, so it tells me I have some more to learn about .should() cy.get('.check-box-sub-text').should('not.exist');
Well this seems to work, so it tells me I have some more to learn about .should()
See lessUpdate value while using byte offset and width numerically
And I believe it means that we skip first 8 bites and then take 16 bits and then we add new value before it. I'm not 100% sure too –
And I believe it means that we skip first 8 bites and then take 16 bits and then we add new value before it. I’m not 100% sure too
See less–
How to replace img tag with pitcure tag in summernote?
You can create a picture tag straight from the string, that is obvously unsafe. const picture = $(`<picture> <source media="(min-width: 400px)" srcset="uploads/large/JS60y3eMKG.webp" type="image/webp"> <source media="(max-width: 300px)" srcset="uploads/medium/JS60y3eMKG.webp" type="imRead more
You can create a picture tag straight from the string, that is obvously unsafe.
And just insert it like you did with an image
$('#summernote').summernote("insertNode", picture[0])
It would be safer to split them into components.
Now you can iterate through your ajax response and dynamically create and add new source’s to a picture.
See lessHow can I pivot a dataframe?
We start by answering the first question: Question 1 Why do I get ValueError: Index contains duplicate entries, cannot reshape This occurs because pandas is attempting to reindex either a columns or index object with duplicate entries. There are varying methods to use that can perform a pivot. SomeRead more
We start by answering the first question:
Question 1
This occurs because pandas is attempting to reindex either a
columns
orindex
object with duplicate entries. There are varying methods to use that can perform a pivot. Some of them are not well suited to when there are duplicates of the keys in which it is being asked to pivot on. For example. Considerpd.DataFrame.pivot
. I know there are duplicate entries that share therow
andcol
values:So when I
pivot
usingI get the error mentioned above. In fact, I get the same error when I try to perform the same task with:
Here is a list of idioms we can use to pivot
pd.DataFrame.groupby
+pd.DataFrame.unstack
unstack
the levels that you want to be in the column index.pd.DataFrame.pivot_table
groupby
with more intuitive API. For many people, this is the preferred approach. And is the intended approach by the developers.pd.DataFrame.set_index
+pd.DataFrame.unstack
groupby
paradigm, we specify all columns that will eventually be either row or column levels and set those to be the index. We thenunstack
the levels we want in the columns. If either the remaining index levels or column levels are not unique, this method will fail.pd.DataFrame.pivot
set_index
in that it shares the duplicate key limitation. The API is very limited as well. It only takes scalar values forindex
,columns
,values
.pivot_table
method in that we select rows, columns, and values on which to pivot. However, we cannot aggregate and if either rows or columns are not unique, this method will fail.pd.crosstab
pivot_table
and in its purest form is the most intuitive way to perform several tasks.pd.factorize
+np.bincount
pd.get_dummies
+pd.DataFrame.dot
Examples
What I’m going to do for each subsequent answer and question is to answer it using
pd.DataFrame.pivot_table
. Then I’ll provide alternatives to perform the same task.Question 3
pd.DataFrame.pivot_table
fill_value
is not set by default. I tend to set it appropriately. In this case I set it to0
. Notice I skipped question 2 as it’s the same as this answer without thefill_value
aggfunc='mean'
is the default and I didn’t have to set it. I included it to be explicit.pd.DataFrame.groupby
pd.crosstab
Question 4
pd.DataFrame.pivot_table
pd.DataFrame.groupby
pd.crosstab
Question 5
Notice that for
pivot_table
andcrosstab
I needed to pass list of callables. On the other hand,groupby.agg
is able to take strings for a limited number of special functions.groupby.agg
would also have taken the same callables we passed to the others, but it is often more efficient to leverage the string function names as there are efficiencies to be gained.pd.DataFrame.pivot_table
pd.DataFrame.groupby
pd.crosstab
Question 6
pd.DataFrame.pivot_table
we passvalues=['val0', 'val1']
but we could’ve left that off completelypd.DataFrame.groupby
Question 7
pd.DataFrame.pivot_table
pd.DataFrame.groupby
Question 8
pd.DataFrame.pivot_table
pd.DataFrame.groupby
pd.DataFrame.set_index
because the set of keys are unique for both rows and columnsQuestion 9
pd.DataFrame.pivot_table
pd.DataFrame.groupby
pd.crosstab
pd.factorize
+np.bincount
pd.get_dummies
Question 10
DataFrame.pivot
The first step is to assign a number to each row – this number will be the row index of that value in the pivoted result. This is done using
GroupBy.cumcount
:The second step is to use the newly created column as the index to call
DataFrame.pivot
.DataFrame.pivot_table
Whereas
DataFrame.pivot
only accepts columns,DataFrame.pivot_table
also accepts arrays, so theGroupBy.cumcount
can be passed directly as theindex
without creating an explicit column.Question 11
If
columns
typeobject
with stringjoin
else
See lessformat
Search Bar Is Not In Coded Position HTML
<!DOCTYPE html> <html> <head> <meta name="viewport" content="width=device-width, initial-scale=1"> <style> * {box-sizing: border-box;} body { margin: 0; font-family: Arial, Helvetica, sans-serif; } .topnav { overflow: hidden; background-color: #e9e9e9; } .topnav a { floRead more
How to iterate each row according to values of row above?
The job essentially seems to be filling missing values by a previous value if such value exists at that measurement for each climber, so groupby.ffill should do the job: out = df[['Name']].join(df.groupby('Name').ffill()) Output: Name Timestamp Category Body Temp Altitude Heart Rate 0 Cody 08:10:23Read more
The job essentially seems to be filling missing values by a previous value if such value exists at that measurement for each climber, so
groupby.ffill
should do the job:Output:
See less