Another simple way is to use the pandas.DataFrame.pivot function to format the data. Use pandas.DataFrame.plot to plot. Providing the colors in the ‘color’ column exist in matplotlib: List of named colors, they can be passed to the color parameter.
To get all indices that matches ‘Smith’ or as a numpy array or if there is only one and you want the integer, you can subset You could use the same boolean expressions with .loc, but it is not needed unless you also want to select a certain column, which is redundant when you only … Read more
You can use boolean indexing: It’s also possible to invert mask by ~:
If you have a DataFrame with only one row, then access the first (only) row as a Series using iloc, and then the value using the column name:
It’s happening because your last column is empty so this becomes converted to NaN: If you slice your range up to the last row then it works: Alternatively you can just select the cols that are object dtype and run the code (skipping the first col as this is the ‘Name’ entry):
You can use pyplot.matshow() from matplotlib: Edit: In the comments was a request for how to change the axis tick labels. Here’s a deluxe version that is drawn on a bigger figure size, has axis labels to match the dataframe, and a colorbar legend to interpret the color scale. I’m including how to adjust the size and rotation … Read more
you could also try; Do note that this will cause the offending lines to be skipped.
You can simply use DataFrame.fillna to fill the nan‘s directly: The docstring of fillna says that value should be a scalar or a dict, however, it seems to work with a Series as well. If you want to pass a dict, you could use df.mean().to_dict().
This will work: But for clarity, I’d probably write it as: