If the X-axes are arranged in the same way, the two figures have the same shape proportion and different connotations. The difference is:

(1) The calculation rules are different. When the horizontal classified variables in histogram ii are represented as quantitative data in histogram I, the interval of each classification is not considered when the classified variables participate in the operation, but the interval of quantitative data has mathematical significance. Quantitative data can be calculated, but classified data cannot be calculated. Quantitative data has one more operational level than classified data.

(2) The meaning of column height is different. The height of histogram ii represents an absolute number, and histogram I is relative in frequency density and weight, so histogram ii is greatly influenced by sample size, and there is no comparability between different samples, but histogram I does not have this problem.

(3) The fitting of sample distribution is different. The curve formed by connecting the vertices of each column in histogram I is the probability density curve of known samples. By mastering the probability density curve, we can calculate the dispersion degree of samples (investigating process capability, discreteness, quality control, etc.). ) and the properties of each quantile. For the curve formed by connecting the vertices of columns with column diagram ii, it is a curve that develops and changes according to classification. It is neither a trend line nor a density curve, and can only be used as a comparison between different classifications.

Generally speaking, the limitations of the column chart are still a little big. I also have a little knowledge. I hope it will help you a little.