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Use Series.map by id by Series from df_2 and then subtract by Series.sub with specified fill_value=0 for same value if no match:

You can use the built in methods to convert those properties to dates:

I have not tested as I don't have sample data.

Try below queries.

From the documentation available in this site https://dev.mysql.com/doc/c-api/5.7/en/mysql-fetch-row.html

When used after mysql_store_result(), mysql_fetch_row() returns NULL if there are no more rows to retrieve.

so use that to verify whether the data has rows or not. Since doing this once would have fetched a row already, you need to print them immediately before trying to get another row from the DB.

1. Low variability on your X means that you'll have less precision in your estimates, but that doesn't seem to be a problem as your coefficient's variations are already low. For more information, look into this CrossValidated post.

2. It's very hard that you don't have an omitted variable that affects you Y, given the very complex nature of what determines GDP, and how hard is to condense all the political and economic characteristics into two indexes. As this indexes have a lot of things inside them, it's also hard to interpret them (the "effect of a gain of 1 on the idex of political transformation on the GDP" isn't much clear). Having said this, if you're not too much concerned with this fact, and you think that the indexes are well made, then they should capture the affects that the economics and politics characteristics have on the GDP. There can be other dimensions that you could want to look into, such as institutions.

3. From the plot, they wouldn't be different if one of the lines were contained in the other's confidence interval (grey area), which is not true. In the summary, you can see that both the coefficient associated with the interaction (slope of the lines) and with the dummy (intercept of the lines) are significantly different than 0.

You have to use conditional cluases. This will allow you to add more stuff to your query if an expression is true.

So, following your example, you would have something like:

Your expression looks like the following:

The order of terms in the polynomial in the numerator goes from -1 to 3 while the denominator goes from 0 to 3. This means that it is bottom-heavy and you will get a 1/s term. This means that there does not exist constants a, b, c, d, e such that polin == (a)*s^4+ (b)*s^3+ (c)*s^2 + (d)*s + (e).

The best you can do is an approximation using a series expansion. It is important to note that one of the terms is 1/s and so you will get something of the form (a)*s^4+ (b)*s^3+ (c)*s^2 + (d)*s + (e) + (f)/s.

To solve this, you could manually get the coefficients or multiply polin by s so that all powers are nonnegative.

Method 1:

A few things for this. Using the __InstanceOperationEvent class is going to give you all create, delete, and modification events for the namespace. This means any time any property on the process instance changes, such as memory (which happens frequently), you'll receive a event to be handled. That's why you are getting so many events being raised.

The other thing I noticed is that your startWatch and stopWatch code share the same query. This means that you are going to receive duplicate events anyway even if the WMI events were only being raised on creation and deletion. You can combine these into one object and event handler then handle which kind of event is being processed in your code like below.

With below query able to replace the filed value.