Ranzcr

Tutorial of Ranzcr EDA

Programming, Python, Kaggle, Ranzcr

강의 홍보

Competition

Intro

import os

import pandas as pd

from matplotlib import pyplot as plt
import seaborn as sns

Check File Size

  • Check Each Size of Dataset Folder in this competition
    • train_records = 4.5GB
    • test_tfrecords = 0.5MB
    • train (image data) = 6.5GB
    • test (image data) = 0.8MB
import os

def get_folder_size(file_directory):
  # file_list = os.listdir(file_directory)
  dir_sizes = {}
  for r, d, f in os.walk(file_directory, False):
      size = sum(os.path.getsize(os.path.join(r,f)) for f in f+d)
      size += sum(dir_sizes[os.path.join(r,d)] for d in d)
      dir_sizes[r] = size
      print("{} is {} MB".format(r, round(size/2**20), 2))      
  
base_dir = '../input/ranzcr-clip-catheter-line-classification'
get_folder_size(base_dir)

../input/ranzcr-clip-catheter-line-classification/test is 805 MB
../input/ranzcr-clip-catheter-line-classification/test_tfrecords is 555 MB
../input/ranzcr-clip-catheter-line-classification/train_tfrecords is 4563 MB
../input/ranzcr-clip-catheter-line-classification/train is 6592 MB
../input/ranzcr-clip-catheter-line-classification is 12524 MB

Check train file

  • Let’s descirbe train
train = pd.read_csv('../input/ranzcr-clip-catheter-line-classification/train.csv', index_col = 0)
test = pd.read_csv('../input/ranzcr-clip-catheter-line-classification/sample_submission.csv', index_col = 0)
display(train.head())
display(test.head())
ETT - Abnormal ETT - Borderline ETT - Normal NGT - Abnormal NGT - Borderline NGT - Incompletely Imaged NGT - Normal CVC - Abnormal CVC - Borderline CVC - Normal Swan Ganz Catheter Present PatientID
StudyInstanceUID
1.2.826.0.1.3680043.8.498.26697628953273228189375557799582420561 0 0 0 0 0 0 1 0 0 0 0 ec89415d1
1.2.826.0.1.3680043.8.498.46302891597398758759818628675365157729 0 0 1 0 0 1 0 0 0 1 0 bf4c6da3c
1.2.826.0.1.3680043.8.498.23819260719748494858948050424870692577 0 0 0 0 0 0 0 0 1 0 0 3fc1c97e5
1.2.826.0.1.3680043.8.498.68286643202323212801283518367144358744 0 0 0 0 0 0 0 1 0 0 0 c31019814
1.2.826.0.1.3680043.8.498.10050203009225938259119000528814762175 0 0 0 0 0 0 0 0 0 1 0 207685cd1
ETT - Abnormal ETT - Borderline ETT - Normal NGT - Abnormal NGT - Borderline NGT - Incompletely Imaged NGT - Normal CVC - Abnormal CVC - Borderline CVC - Normal Swan Ganz Catheter Present
StudyInstanceUID
1.2.826.0.1.3680043.8.498.46923145579096002617106567297135160932 0 0 0 0 0 0 0 0 0 0 0
1.2.826.0.1.3680043.8.498.84006870182611080091824109767561564887 0 0 0 0 0 0 0 0 0 0 0
1.2.826.0.1.3680043.8.498.12219033294413119947515494720687541672 0 0 0 0 0 0 0 0 0 0 0
1.2.826.0.1.3680043.8.498.84994474380235968109906845540706092671 0 0 0 0 0 0 0 0 0 0 0
1.2.826.0.1.3680043.8.498.35798987793805669662572108881745201372 0 0 0 0 0 0 0 0 0 0 0

Definitions of Variables

  • What’s inside data?
    • StudyInstanceUID - unique ID for each image
    • ETT - Abnormal - endotracheal tube placement abnormal
    • ETT - Borderline - endotracheal tube placement borderline abnormal
    • ETT - Normal - endotracheal tube placement normal
    • NGT - Abnormal - nasogastric tube placement abnormal
    • NGT - Borderline - nasogastric tube placement borderline abnormal
    • NGT - Incompletely Imaged - nasogastric tube placement inconclusive due to imaging
    • NGT - Normal - nasogastric tube placement borderline normal
    • CVC - Abnormal - central venous catheter placement abnormal
    • CVC - Borderline - central venous catheter placement borderline abnormal
    • CVC - Normal - central venous catheter placement normal
    • Swan Ganz Catheter Present(??)
    • PatientID - unique ID for each patient in the dataset

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