U17 | iOS componentization and responsive construction
kandi X-RAY | U17 Summary
kandi X-RAY | U17 Summary
iOS componentization and responsive construction have Yaoqi comics (v4.3.12), which are continuously updated.
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QUESTION
I have such a dataframe df_new
with index column name
and column length
:
ANSWER
Answered 2021-May-16 at 14:10I think the error is coming from this line because ind = df_new['name']
makes ind
a string, and you cannot add a number to it:
QUESTION
I'm looping through an API response and displaying some items (female and male age groups) on a page with the following code:
...ANSWER
Answered 2021-Jan-18 at 19:48[class.is-active]
needs to 'bind' to a value, it is unclear to me the intent of what you trying to do as a whole, but, each age group needs a state. Thus, you need to update/modify your data either from the server or augment in your component with the status for each age group...
QUESTION
I have a spark SQL string like this:
...ANSWER
Answered 2021-Jan-15 at 07:03Now use the following syntax and it works:
QUESTION
My goal with the following code is to create an athlete object and override the save method to automatically set the category
for a given athlete based on the born_date
.
The Category
class will be inherited in other models too. The list within the class serves as validation purposes for the save method and the tuples for choice fields (used in other models).
Although everything seems right, I ran some test in the shell and the code is saving whatever born_date
is inputed. Why is that the case? Can someone shed some light on the problem? Thanks
ANSWER
Answered 2020-Aug-29 at 13:34Do not assign category value to the object if you do not want to save it, I made some changes to your code.
Try to do like this:
QUESTION
I have a dictionary of user ratings stored in a user_dict dictionary which looks like this:
...ANSWER
Answered 2020-Aug-10 at 11:12You can reshape by DataFrame.unstack
with DataFrame
construcot, then filtering out 0
by compare for not equal, set index names for new columns names and last use Series.reset_index
:
QUESTION
I am building a recommender system based on user's ratings for 11 different items.
I started with a dictionary (user_dict) of user ratings:
...ANSWER
Answered 2020-Aug-07 at 14:12The problem is coming from the way you are converting your dictionary into a pandas dataframe. For the Dataset to be able process a pandas dataframe, you will need to have only three columns. First column is supposed to be the user ID, second column is the item ID and the third column is the actual rating. This is how I would build a dataframe which would run in "Dataset":
QUESTION
I am converting my Python dictionary of "user-ratings" into a Pandas dataframe.
Here is the dictionary (user_dict) for reference:
...ANSWER
Answered 2020-Aug-05 at 21:17You don't need to give keys when you are converting dictionary to dataframe. The dictionary keys are taken as columns.
QUESTION
I am learning about pipes and forks. I am trying to get the count of kworker processes by using pipes and forks to represent ps -A | grep kworker | wc -l
. My code is working correctly until the point where I am doing the pipes for the grep statement.
I run my code like this: ./a.out kworker
ANSWER
Answered 2020-Jul-15 at 09:37Look:
QUESTION
I have a technical question related to my df structure. It looks like this:
...ANSWER
Answered 2020-Jun-23 at 14:06You can use an ANOVA test to compare multiple groups. If you find any statistically significant results with the omnibus ANOVA test, then you can check which district is different better or worse.
You can also refer to UCLA's website that shows which tests one should use to test their data. The link is here.
As a quick example, let me put here how to run an ANOVA test.
Here is your data:
QUESTION
So I have a medium size database with 113K rows X 14 columns
...ANSWER
Answered 2020-Jun-16 at 17:03Consider your data as df
. Then I have added some dummy districts named Bob and John. Also, I have only considered the first 5 occupations for this example. A bar chart code is given below:
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