jkm2000korea / data_visualization

data_visualization

Stem plot

Plotly_3d_plots

Bot plot with dots

Animated histogram

Analysis of average lunch time data by department

Hexagonal talent

Hexagonal company

Cumulative distribution

To change colors with if condition clause

['green' if y > 0 else 'red' for y in y_values]

McKinsey Priority Matrix based on Scatter maskted from matplotlib

To draw bubble chart with 3 variables

To make construction time line chart using chatGPT

even though the order of construction and duration is not right, it can be revised with domain knowledge

Time line Chart

to make 3 variables one(1) and use iteration with zip(dates, levels, names)

Bar color demo

Bar_label_demo

To stack bars one one another giving argument of "bottom"

Horizontal bar chart

To add "error bar" giving argument of "xerrr"

Bar_Stacked

for iteration "boolean, count" in array.items():

Bar_Grouped

To control the space with "offset" in x data argument

fill_between

to fill some region between two lines with colors, use "fill_between(base_axis, upper line, lower line, where condition)"

Staked horizontal bar chart

To draw a stacked bar, use the function of ax.barh(labels, widths, left=starts...). Argument "left" has the same role as "bottom" in ax.bar function

Bot plot vs. Scatter plot

The difference between them is violin plots show the whole range of the data with the distribution function is nothing special. violinplot(), boxplot()