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Bar graphs can also be used for more complex comparisons of data with grouped (or "clustered") bar charts, and stacked bar charts. [5] In grouped (clustered) bar charts, for each categorical group there are two or more bars color-coded to represent a particular grouping. For example, a business owner with two stores might make a grouped bar ...
and you can see that b, as visible from the closure's scope, retains the value it had; the changed binding of b inside the inner function did not propagate out. The way around this is to use a nonlocal b statement in bar. In Python 2 (which lacks nonlocal), the usual workaround is to use a mutable value and change that value, not the binding. E ...
Each bar can also have a comment, such as "comment7=xx" to show "(xx)" after the number in bar 7. For a 2-column bar chart, the 2nd column items have prefix "col2_" such as scale maximum, col2_data_max=110, and col2_data3=67 with col2_comment3=zz. See below: "Example with two data columns". Each bar chart can be formatted typically within 1/5 ...
An OHLC chart, with a moving average and Bollinger bands superimposed. An open-high-low-close chart (OHLC) is a type of chart typically used in technical analysis to illustrate movements in the price of a financial instrument over time. Each vertical line on the chart shows the price range (the highest and lowest prices) over one unit of time ...
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Candlestick charts serve as a cornerstone of technical analysis. For example, when the bar is white and high relative to other time periods, it means buyers are very bullish. The opposite is true when there is a black bar. A candlestick pattern is a particular sequence of candlesticks on a candlestick chart, which is mainly used to identify trends.
In the analysis of data, a correlogram is a chart of correlation statistics. For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram.
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