Moving average is a powerful technique to smooth out variations in temporal trend and is done by taking an average of pa

Time series data is best analyzed and understood through visualization. We can write all the codes to do resampling and moving averages etc. and create new data frames all we want but in the end, we can’t understand anything until they are visualized.

While Jeff Bezos was building Amazon from a garage into one of the most powerful companies on earth and becoming the richest businessmen of this age, the world knew very little about his wife, MacKenzie, a novelist and a mother of four who helped start Amazon from that garage. Even after their divorce last year, accompanied by a public affair and scandal, thrust MacKenzie Scott (the name she took after the split) into the spotlight, she remained a private and elusive figure. Now, Scott, one of the richest women in the world, a billionaire tens times over, announced in July that she was giving away $1.7 billion to a wide swath of nonprofits, from historically Black colleges to a crisis text line. The gift was stunning in scale and in approach: Scott was making a mark as a new kind of philanthropist.

Below is a sample of 8 different techniques for visualization. Is that all you need to know? The short answer is — if you know how to create and interpret these 8 visualizations, you are in pretty good shape!

The purpose of this article was to put in one place most of the data wrangling and visualization techniques you’d need as a beginner or intermediate time series analyst. First, we saw how to convert an ordinary dataframe into a powerful datetime object and put that into use for filtering and visualizing. In the second part, we’ve created 8 different plots using different techniques to visualize time series. The next step would be to go ahead and pick a different dataset, reproduce the results and play with different plotting parameters.

At the same time, Scott has drawn some criticism for the opaque nature of her giving and for the source of her great wealth: Amazon, which has grown during the pandemic to a nearly $1.6 trillion market cap in early October, and has become notorious for paying relatively little in corporate taxes.

The purpose of this article was to put in one place most of the data wrangling and visualization techniques you’d need as a beginner or intermediate time series analyst. First, we saw how to convert an ordinary dataframe into a powerful datetime object and put that into use for filtering and visualizing. In the second part, we’ve created 8 different plots using different techniques to visualize time series. The next step would be to go ahead and pick a different dataset, reproduce the results and play with different plotting parameters.

I am not going to write complex codes to create beautiful figures, instead, use the default seaborn parameters in one-liner codes. As an individual, you can customize these figures however you wish based on your taste and sense of beauty!

Moving average is similar to resampling but has more flexibility, you can specify any number of past observations as a rolling window. Below is an example using a moving window of 6 past observations.

Last, but not least, remember we’ve created wide-form data in the beginning and now it’s time to put that into use. Using the visualization technique below we are now seeing trends in data for each month separately.

Bill Gates Enters His Third Act: Ruthless Nerd Savior After going from relentless competitor to sweater-wearing do-gooder, he’s becoming the merciless samaritan we needmarker.medium.com

With that, Scott far outpaced her ex-husband in the giving realm, and rewrote the typical playbook for high-profile tech philanthropists — who often operate as if they know best not just in business, but in solving societal problems, too. “Their engineering or technocratic orientation to their business, their wealth creation, transfers over to their philanthropic practices,” says Rob Reich, a Stanford political science professor, referring to tech superstars like Mark Zuckerberg or Bill Gates. “To put it really crudely, technocratic philanthropy is philanthropy that is done to people rather than with people.”

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ed vision and prioritize: Don’t sweat the small stuff and keep the focus on spending time together alone and with your kids. For instance, in our house we have pizza on Tuesday nights and eat at a restaurant twice a month. This gives us six nights a month to spend more time together when we aren’t so focused on cooking and cleaning up.

In any exploratory data analysis, boxplots are the most useful statistical graphics to understand both the central tendency and the distribution of data. It is somewhat similarly useful in time series data. Below is an example of monthly boxplots of values.

Scott gave 116 grants, all at once, with very few strings attached, to mostly small organizations. They didn’t have to hit metrics she named; they didn’t have to create programs she favored. She even refused thank you notes when nonprofits asked how they could show their gratitude. And she specifically chose organizations led by people with “lived experience,” as Scott put it: women leading women’s groups, people of color leading racial equity groups.

With a gift of that size, Scott could’ve built a cancer center, had a museum wing named after her, made a college rededicate itself in her name. Or, like virtually every other person who’s made significant amounts of money from tech, she could’ve created an organization to dole out grants based on her notions about how best to fix social issues. She chose another route.