Try starting Jupyter Notebook ~ Esper training

Until Jupyter Notebook starts

--It is difficult to categorize this article ――I don't know what the problem is in the first place, so I can't decide the title or category first.

Imagine the environment

I could have imagined it because it was pasted in the image, is it jupyter as expected?

• https://qiita.com/fuku_tech/items/6752b00770552bf4f46b
• https://qiita.com/littlem/items/4893bc46bbdff4f97dfb

docker-compose.yml

version: '3'
services:
  jupyter:
    image: jupyter/scipy-notebook
    ports:
      - 10000:8888
    volumes:
      - $PWD:/home/jovyan/work
    command: start.sh jupyter lab --NotebookApp.token=''

$ docker-compose up

Go to http: // localhost: 10000 / and look at the console.

Try

I'd be happy if someone had the code when trying it, but I didn't have it so I hit it by hand

Source 1

data = {'name': ['Ryo', 'Kaori', 'Hideyuki', 'Hayato', 'Miki', 'Saeko'],
        'gender': ['M', 'F', 'M', 'M', 'F', 'F'],
        'height': [186, 168, 175, 210, 160, 163],
        'weight': [72, 47, 62, 90, None, numpy.NaN],
        'age': [30, 20, None, numpy.NaN, 23, 25],
        'size': ['L', 'M', 'L', 'XL', None, 'S']
        }

error

NameError: name 'numpy' is not defined

• Solve
  • https://pythondatascience.plavox.info/numpy

After modification 1

import numpy
data = {'name': ['Ryo', 'Kaori', 'Hideyuki', 'Hayato', 'Miki', 'Saeko'],
        'gender': ['M', 'F', 'M', 'M', 'F', 'F'],
        'height': [186, 168, 175, 210, 160, 163],
        'weight': [72, 47, 62, 90, None, numpy.NaN],
        'age': [30, 20, None, numpy.NaN, 23, 25],
        'size': ['L', 'M', 'L', 'XL', None, 'S']
        }

Try it 2

Source 2

size2int = {'S': 1, 'M': 2, 'L': 3, 'XL': 4}
df['size'] = df['size'].map(size2int)
df

error

NameError: name 'df' is not defined

Well, that's right

• https://qiita.com/simonritchie/items/d7dccb798f0b9c8b1ec5

After modification 2

import pandas as pd
df = pd.DataFrame(data)
#size2int means size to int
size2int = {'S': 1, 'M': 2, 'L': 3, 'XL': 4}
df['size'] = df['size'].map(size2int)
df

It's done. Why doesn't it work? Insufficient esper power.

Esper

The expectation is that I overwrote the size column once with size2int missing. After that, it is only NaN.

sample

size2int = {'Ｓ': 1, 'Ｍ': 2, 'Ｌ': 3, 'ＸＬ': 4}

Like

Then, let's try data → df again. Is something.

Really?

Fail once

import pandas as pd
df = pd.DataFrame(data)
size2int = {}
df['size'] = df['size'].map(size2int)
df

No matter how many times I do it

size2int = {'S': 1, 'M': 2, 'L': 3, 'XL': 4}
df['size'] = df['size'].map(size2int)
df

Can be reproduced for the time being

Add WIP Esper power

• pandas.DataFrame
  • https://note.nkmk.me/python-pandas-dataframe-values-columns-index/
• map

Summary

――Mostly you stumble where it doesn't really matter ――It is surprisingly important to create an environment where you can try it from the beginning ――Docker is convenient when you want to create an environment quickly. Because it is a code, you can pass it