This is going to have a lot of memes.
Whenever I think of Pandas, I picture myself gearing up for the eventual adrenaline rush. Working with data can be a pleasant, fantastic, immersive experience- but it is not for the feeble hearted.
I cannot tell the days I have squealed with absolute delight to find a pattern that might be useful in my research. This is almost always followed by a victory jig.
There are days when I get so pleased with myself on figuring out a nuance that would have gone unnoticed if it hadn't been for my clever and careful inspection, only to discover (mostly when I am treating myself with an ice cream) that I had done something horribly wrong.
And then, there are the days I have crashed and burned because my computer had just placidly displayed a p-value of 0.98, thus invalidating months of work. I might not be the first one to say this, but I suppose when Fisher first popularized p-values, he would have never thought about how intricately his p-values are going to be tied with a grad student's self-worth.
In my head, the whole idea with data is a scavenger hunt. You have millions of corners where exciting things may or may not hide. This kind of digging appeals to the crazy deal seeker in me and I tell myself that this is why I love this gig. But there are times of almost cruel disappointments - for example, you would expect something fun to lie beneath 1 TB of data, which is always not the case. You just keep ploughing through hoping for your "high fiving a million angels moment". The uncertainty is a rush, but once you see the ugly side, you always know that things can go terribly wrong.
So when I think of Pandas I always steel myself for disappointments. It always feels like I am walking into a battlefield, like this.
This is also Pandas - Just the cute and the cuddly kind!
Whenever I think of Pandas, I picture myself gearing up for the eventual adrenaline rush. Working with data can be a pleasant, fantastic, immersive experience- but it is not for the feeble hearted.
I cannot tell the days I have squealed with absolute delight to find a pattern that might be useful in my research. This is almost always followed by a victory jig.
There are days when I get so pleased with myself on figuring out a nuance that would have gone unnoticed if it hadn't been for my clever and careful inspection, only to discover (mostly when I am treating myself with an ice cream) that I had done something horribly wrong.
And then, there are the days I have crashed and burned because my computer had just placidly displayed a p-value of 0.98, thus invalidating months of work. I might not be the first one to say this, but I suppose when Fisher first popularized p-values, he would have never thought about how intricately his p-values are going to be tied with a grad student's self-worth.
In my head, the whole idea with data is a scavenger hunt. You have millions of corners where exciting things may or may not hide. This kind of digging appeals to the crazy deal seeker in me and I tell myself that this is why I love this gig. But there are times of almost cruel disappointments - for example, you would expect something fun to lie beneath 1 TB of data, which is always not the case. You just keep ploughing through hoping for your "high fiving a million angels moment". The uncertainty is a rush, but once you see the ugly side, you always know that things can go terribly wrong.
So when I think of Pandas I always steel myself for disappointments. It always feels like I am walking into a battlefield, like this.
But then I came across this video today and this is the first time I think of Pandas without getting riled up.
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