Pandas for Productivity Vlog Ep 5: Moving averages in Pandas
Why this topic? This topic doesn’t have much documentation, yet is potentially very useful. Calculating moving averages in Excel is […]
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Pandas
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Pandas for Productivity Vlog Ep2: Think like a data engineer!
Why this topic? When we join two flat files, or a flat file to a SQL query output in Python,
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Sort and rank data with pandas
Businesses like to know what their top-performing products, markets, and segments are. Therefore, you’ll need to sort and rank data
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Combine data sets by merging or concatenating
Have you ever tied up your computer for hours with a vlookup? Or laboriously copy pasted rows of .csv data
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Grouping and aggregating data in pandas
Most business questions involve grouping and aggregating data. For example, we might want to examine sales by product category. Or
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Handle missing values in your DataFrame
When will you get missing values in your data? Quite often, actually! For instance, customer survey data where respondents did
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How to filter a DataFrame: Focus on specific data
In the past few posts, we’ve discussed how to read your data into pandas, and then manipulate it via calculations.
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Working with date and time in Pandas
When looking at business data, time is always an important factor. From the start, you will focus on pulling your
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Rename columns in your DataFrame
Humans and computers like their text set up in different ways. For humans, you want familiar terms with capital letters