ltp | This software is licensed under the Apache

Please share a small example of the dataset you are working on to help understand the question better. I'm not sure what are the rows and columns in your data set.

Basics to get around in pandas:

• df['column_name'] - returns a subset of your data set just with column

• df.loc['row_index','column_name'] - returns a value from a column and row using column name and row_index

in your case, I think it will be:

• stock.loc[symbol, 'Open'] - if Open is a column and symbols are in rows

or

• stock.loc['Open', symbol]- if symbols are in columns and Open is a row

Based on the comments, I can see that both Symbol and Open are columns, try this:

A couple of things.

You can make the clicked item span two rows by setting grid-row: span 2 This will have the effect of 'pushing' other grid items around.

In the JS you had a call to remove which I think should have been removeClass

Here's a (slightly messy) SO snippet created from your codepen:

The problem is classloader shenanigans, no doubt.

You have 2 separate classes coincidentally both named com.ltp.analog.core.annotation.Component. They aren't the same thing even though they have the same name.

Come again? Yes, really.

Imagine this code:

GitHub doesn't support Git hooks (on GitHub.com at least, they are supported on GitHub Enterprise). However, you can use GitHub Actions to run arbitrary code on a push, albeit in an isolated VM and not on the actual Git server.

In .github/workflows/wiki-mirror.yml (or whatever filename you want in .github/actions), you can add an Action to do the syncing. Since GitHub wikis expect markdown files, this changes the extensions of the .txt files to match:

It seems like you are trying to attach the datetime column of the same length to the OHLC dataframe. axis=0 is for rows while axis=1 is for columns. By default, pandas uses axis=0, so you need to specify your preferred change to axis=1.

Try changing your concat to this:

.append(sdata) appends data (unsurprisingly :) )

If you don't want to append, but replace the whole thing, use .html(sdata).

Updated fiddle

Use np.sign with selected columns first, then counts values in value_counts, transpose, replaced missing values and last rename columns names by dictionary with convert index to column columns:

The error is because you are defining open as open = group['ltp'].iloc[0] earlier in the code and then later on trying to do a with open('C:/Users/choud/Documents/'+symbol+'.csv','a') as f_object:

Effectively, you have redefined open and it can no longer be used to open a file.

The following was run using

• MySQL Server version: 8.0.25 MySQL Community Server
• Sequelize version 6.6.5

Summary

Timestamps: The values returned from the .bulkCreate method can be misleading. You will need to query for the items after doing a bulkUpdate to find the new values. To quote the sequelize docs for version 6:

The success handler is passed an array of instances, but please notice that these may not completely represent the state of the rows in the DB. This is because MySQL and SQLite do not make it easy to obtain back automatically generated IDs and other default values in a way that can be mapped to multiple records. To obtain Instances for the newly created values, you will need to query for them again.

Also, to update the updatedAt column, it will need to be included in the array parameter for updateOnDuplicate. Otherwise, it will not receive a new timestamp.

Non-sequential primary keys: The next auto_increment value for the MySQL primary key appears to be incremented when an update is being done. I'm not really sure if there's a way to prevent this from happening. However, it is still possible to insert rows that have primary keys which have been skipped over by the auto_increment mechanism. Also, according to another answer on stackoverflow concerning non-sequential primary keys, there should be no impact on efficiency. As an alternative, bulkCreate statements could be separated into two groups, one for inserts and one for updates, which could then be done separately using sequelize. The downside is that there would be extra queries to determine whether incoming data already exists in the database in order to decide between inserts versus updates.

Here's a code sample: