Q01. Age

Q01. Age#

Question#

What is your age?

Choices#

  1. 10s (less than 19 yeas old)

  2. 20s

  3. 30s

  4. 40s

  5. 50s

  6. 60s

  7. 70s

  8. 80s

  9. 90s+ (more than 90 years old)

Responses#

import pandas as pd

import titanite as ti

print(f"Pandas: {pd.__version__}")
print(f"Titanite: {ti.__version__}")
Pandas: 3.0.2
Titanite: 0.7.0
f_cfg = "../../../sandbox/config.toml"
f_csv = "../../../data/test_data/prepared_data.csv"
d = ti.Data(read_from=f_csv, load_from=f_cfg)
config = d.config()
data = d.read()
2026-05-11 20:43:07.374 | ERROR    | titanite.config:load_toml:87 - File not found: ../../../sandbox/config.toml
---------------------------------------------------------------------------
Exit                                      Traceback (most recent call last)
Cell In[2], line 4
      1 f_cfg = "../../../sandbox/config.toml"
      2 f_csv = "../../../data/test_data/prepared_data.csv"
      3 d = ti.Data(read_from=f_csv, load_from=f_cfg)
----> 4 config = d.config()
      5 data = d.read()

File ~/work/surveys/surveys/titanite/config.py:261, in Data.config(self)
    259 def config(self):
    260     c = Config(load_from=self.load_from)
--> 261     return c.load_config()

File ~/work/surveys/surveys/titanite/config.py:95, in Config.load_config(self)
     94 def load_config(self) -> dict:
---> 95     config = self.load_toml()
     96     return config

File ~/work/surveys/surveys/titanite/config.py:88, in Config.load_toml(self)
     86 if not fname.exists():
     87     logger.error(f"File not found: {fname}")
---> 88     raise typer.Exit(code=1)
     90 with fname.open("rb") as f:
     91     config = tomllib.load(f)

Exit: 
names = ["q01"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)

20代、30代の回答が多かった

Breakdowns#

  • q01と他の質問の内訳を確認した

names = ["q01", "q02"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
  • 30代は、女性の回答比率が高め

names = ["q01", "q03_regional"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q05"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
  • 20代は博士課程

  • 30代はポスドク

  • 40代以上はパーマネント

names = ["q01", "q06"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q07"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q08"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q09"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q11"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q12_genderbalance"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q12_diversity"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q12_equity"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)
names = ["q01", "q12_inclusion"]
bd = ti.analysis.breakdowns(data, names)
bd.graph.cols(1)