language_dependencies_graph.py

from plotnine import *
import pandas as pd
import numpy as np
  
# Initialize list of lists
raw = [['PHP', 9, 70], ['Java', 8, np.nan], ['JavaScript', 10, 683], ['.NET', 3, np.nan], ['Python', 6, 19], ['Ruby', 9, 68]]
data = {
    'Language': [],
    'Type': [],
    'Value': []
}
for elem in raw:
  data['Language'] += [elem[0], elem[0]]
  data['Type'] += ['Direct', 'Indirect']
  data['Value'] += [elem[1], elem[2]]

def no_labels(values):
    return [""] * len(values)

# Create the pandas DataFrame
df = pd.DataFrame(data = data)
dodge_text = position_dodge(width=0.9)

plot = (ggplot(df, aes(x='Language', y='Value', fill='Type'))
+ geom_col(stat='identity', position='dodge')
+ scale_y_log10(labels=no_labels, expand=(0, 0, 0, 1))   
+ geom_text(aes(label='Value'),
             position=dodge_text,
             size=8, va='bottom', format_string='{:0.0f}')
+ theme_minimal()
+ theme(panel_background=element_rect(fill='white'),
        axis_text_y=element_blank(),
        axis_title_y=element_blank(),
        axis_ticks_major_y=element_blank(),
        axis_title_x=element_blank(),
        axis_line_x=element_line(size=1),
        panel_grid_major=element_blank(),
        panel_grid_minor=element_blank(),
        legend_title=element_blank())
)

save_as_pdf_pages([plot])