================ by Jawad Haider

Part 1: Using wget¶

# download the data from a URL
# source: https://archive.ics.uci.edu/ml/datasets/Arrhythmia
# alternate URL: https://lazyprogrammer.me/course_files/arrhythmia.data
#!wget --no-check-certificate https://archive.ics.uci.edu/ml/machine-learning-databases/arrhythmia/arrhythmia.data
!wget https://lazyprogrammer.me/course_files/arrhythmia.data

--2020-04-26 07:33:37--  https://lazyprogrammer.me/course_files/arrhythmia.data
Resolving lazyprogrammer.me (lazyprogrammer.me)... 104.31.80.48, 104.31.81.48, 2606:4700:3035::681f:5130, ...
Connecting to lazyprogrammer.me (lazyprogrammer.me)|104.31.80.48|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 402355 (393K)
Saving to: ‘arrhythmia.data’

arrhythmia.data     100%[===================>] 392.92K  1.09MB/s    in 0.4s

2020-04-26 07:33:38 (1.09 MB/s) - ‘arrhythmia.data’ saved [402355/402355]

# list files in current directory
!ls

arrhythmia.data  sample_data

# check if the data has a header
!head arrhythmia.data

75,0,190,80,91,193,371,174,121,-16,13,64,-2,?,63,0,52,44,0,0,32,0,0,0,0,0,0,0,44,20,36,0,28,0,0,0,0,0,0,52,40,0,0,0,60,0,0,0,0,0,0,52,0,0,0,0,0,0,0,0,0,0,0,0,56,36,0,0,32,0,0,0,0,0,0,48,32,0,0,0,56,0,0,0,0,0,0,80,0,0,0,0,0,0,0,0,0,0,0,0,40,52,0,0,28,0,0,0,0,0,0,0,48,48,0,0,32,0,0,0,0,0,0,0,52,52,0,0,36,0,0,0,0,0,0,0,52,48,0,0,32,0,0,0,0,0,0,0,56,44,0,0,32,0,0,0,0,0,0,-0.2,0.0,6.1,-1.0,0.0,0.0,0.6,2.1,13.6,30.8,0.0,0.0,1.7,-1.0,0.6,0.0,1.3,1.5,3.7,14.5,0.1,-5.2,1.4,0.0,0.0,0.0,0.8,-0.6,-10.7,-15.6,0.4,-3.9,0.0,0.0,0.0,0.0,-0.8,-1.7,-10.1,-22.0,0.0,0.0,5.7,-1.0,0.0,0.0,-0.1,1.2,14.1,22.5,0.0,-2.5,0.8,0.0,0.0,0.0,1.0,0.4,-4.8,-2.7,0.1,-6.0,0.0,0.0,0.0,0.0,-0.8,-0.6,-24.0,-29.7,0.0,0.0,2.0,-6.4,0.0,0.0,0.2,2.9,-12.6,15.2,-0.1,0.0,8.4,-10.0,0.0,0.0,0.6,5.9,-3.9,52.7,-0.3,0.0,15.2,-8.4,0.0,0.0,0.9,5.1,17.7,70.7,-0.4,0.0,13.5,-4.0,0.0,0.0,0.9,3.9,25.5,62.9,-0.3,0.0,9.0,-0.9,0.0,0.0,0.9,2.9,23.3,49.4,8
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55,0,175,94,100,202,380,179,143,28,11,-5,20,?,71,0,72,20,0,0,48,0,0,0,0,0,0,0,64,36,0,0,36,0,0,0,0,0,0,20,52,48,0,0,56,0,0,0,0,0,0,64,32,0,0,0,72,0,0,0,0,0,0,0,60,12,0,0,44,0,0,0,0,0,0,0,60,44,0,0,32,0,0,0,0,0,0,56,0,0,0,0,0,0,0,0,0,0,0,0,40,44,0,0,20,0,0,0,0,0,0,0,52,40,0,0,32,0,0,0,0,0,0,0,56,48,0,0,36,0,0,0,0,0,0,0,60,48,0,0,36,0,0,0,0,0,0,0,64,40,0,0,40,0,0,0,0,0,0,0.9,0.0,7.8,-0.7,0.0,0.0,1.1,1.9,27.3,45.1,0.1,0.0,9.1,-2.6,0.0,0.0,0.4,1.5,24.5,36.8,-0.4,-0.4,1.6,-2.2,0.0,0.0,-1.0,-0.9,-1.5,-9.2,-0.4,-8.2,1.8,0.0,0.0,0.0,-0.7,-1.7,-23.4,-35.6,0.9,0.0,3.2,-0.4,0.0,0.0,0.7,1.2,9.4,18.0,-0.1,0.0,5.1,-2.5,0.0,0.0,0.3,0.6,9.8,12.6,1.6,-6.5,0.0,0.0,0.0,0.0,-0.4,-0.4,-18.2,-22.4,2.1,0.0,1.2,-6.9,0.0,0.0,-0.5,2.9,-12.7,18.0,0.7,0.0,9.0,-7.9,0.0,0.0,0.1,4.1,7.6,51.0,0.4,0.0,15.0,-5.5,0.0,0.0,0.1,3.3,28.8,63.1,0.1,0.0,15.2,-3.7,0.0,0.0,0.6,3.0,36.8,68.0,0.1,0.0,12.2,-2.2,0.0,0.0,0.4,2.6,34.6,61.6,1
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49,1,162,54,78,0,376,157,70,67,7,8,51,?,67,0,44,36,0,0,24,0,0,0,0,0,0,0,52,32,0,0,28,0,0,0,0,0,0,0,56,28,0,0,24,0,0,0,0,0,0,48,32,0,0,0,56,0,0,0,0,0,0,52,0,0,0,0,0,0,0,0,0,0,0,0,52,28,0,0,28,0,0,0,0,0,0,0,20,44,0,0,8,0,0,0,0,0,0,0,24,48,0,0,16,0,0,0,0,0,0,0,36,44,0,0,24,0,0,0,0,0,0,0,44,48,0,0,28,0,0,0,0,0,0,0,48,44,0,0,28,0,0,0,0,0,0,0,48,40,0,0,24,0,0,0,0,0,0,-0.3,0.0,4.1,-1.1,0.0,0.0,0.8,1.0,7.1,13.7,-0.3,0.0,8.4,-1.5,0.0,0.0,0.6,0.7,19.4,22.9,0.0,0.0,4.4,-0.8,0.0,0.0,-0.3,-0.6,11.2,6.9,0.1,-6.3,1.3,0.0,0.0,0.0,-0.6,-0.8,-13.1,-17.9,0.1,-0.8,0.0,0.0,0.0,0.0,0.6,0.7,-2.0,2.9,-0.2,0.0,6.3,-1.2,0.0,0.0,0.2,0.3,14.7,16.8,0.7,0.0,0.5,-7.3,0.0,0.0,0.2,-0.1,-15.5,-16.4,0.9,0.0,0.7,-8.9,0.0,0.0,0.6,2.5,-20.5,4.0,0.8,0.0,2.1,-9.0,0.0,0.0,0.6,3.8,-16.1,21.1,0.1,0.0,6.6,-4.1,0.0,0.0,0.3,1.4,4.7,14.2,-0.2,0.0,8.5,-2.7,0.0,0.0,0.1,0.8,14.5,20.9,-0.3,0.0,8.2,-1.9,0.0,0.0,0.1,0.5,15.8,19.8,1
44,0,168,56,84,118,354,160,63,61,69,78,66,84,64,0,40,0,0,0,20,0,0,0,0,0,0,0,44,12,0,0,28,0,0,0,0,0,0,0,36,8,0,0,20,0,0,0,0,0,0,40,12,0,0,0,44,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,36,12,0,0,20,0,0,0,0,0,0,0,20,56,0,0,12,0,0,0,0,0,0,0,24,48,0,0,12,0,0,0,0,0,0,0,28,44,0,0,16,0,0,0,0,0,0,0,44,32,0,0,32,0,0,0,0,0,0,0,44,28,0,0,28,0,0,0,0,0,0,0,40,24,0,0,24,0,0,0,0,0,0,0.1,0.0,2.3,0.0,0.0,0.0,0.4,1.0,4.6,11.6,1.2,0.0,5.4,-0.7,0.0,0.0,1.8,2.8,11.4,31.0,1.1,0.0,3.0,-0.4,0.0,0.0,1.4,1.8,5.3,17.9,-0.7,-3.9,0.5,0.0,0.0,0.0,-1.1,-1.9,-7.5,-20.4,-0.5,0.0,0.0,0.0,0.0,0.0,-0.6,-0.5,0.0,-3.4,1.1,0.0,4.2,-0.5,0.0,0.0,1.6,2.3,7.2,22.8,0.5,0.0,0.9,-5.5,0.0,0.0,-0.7,1.0,-14.5,-5.3,0.7,0.0,1.2,-6.4,0.0,0.0,-0.5,2.6,-13.9,10.0,1.5,0.0,2.4,-10.3,0.0,0.0,0.3,6.8,-19.3,43.2,0.8,0.0,7.9,-7.3,0.0,0.0,0.9,6.5,5.7,62.9,0.1,0.0,9.3,-3.8,0.0,0.0,0.8,3.8,15.1,48.5,0.1,0.0,7.0,-1.3,0.0,0.0,0.6,2.1,12.5,30.9,1
50,1,167,67,89,130,383,156,73,85,34,70,71,?,63,0,44,40,0,0,28,0,0,0,0,0,0,0,56,24,0,0,32,0,0,0,0,0,0,0,72,0,0,0,28,0,0,0,0,0,0,56,28,0,0,0,60,0,0,0,0,0,0,0,28,56,0,0,16,0,0,0,0,0,0,0,60,0,0,0,32,0,0,0,0,0,0,0,24,36,32,0,68,0,0,0,0,0,0,0,36,44,0,0,20,0,0,0,0,0,0,0,40,48,0,0,24,0,0,0,0,0,0,0,56,40,0,0,40,0,0,0,0,0,0,0,52,36,0,0,32,0,0,0,0,0,0,20,44,36,0,0,44,0,0,0,0,0,0,-0.1,0.0,3.5,-2.0,0.0,0.0,0.4,1.3,3.7,13.5,0.0,0.0,9.9,-0.8,0.0,0.0,1.2,1.2,26.8,35.2,0.0,0.0,8.3,0.0,0.0,0.0,0.8,0.3,29.8,32.0,0.1,-6.1,1.1,0.0,0.0,0.0,-0.6,-1.2,-15.5,-24.1,0.0,0.0,0.6,-4.1,0.0,0.0,-0.1,0.8,-10.6,-4.9,-0.2,0.0,8.9,0.0,0.0,0.0,0.8,0.7,26.7,30.2,0.1,0.0,1.3,-5.4,1.9,0.0,0.2,0.8,-5.2,2.1,0.8,0.0,4.4,-8.5,0.0,0.0,0.8,3.9,-10.8,25.0,0.4,0.0,4.3,-7.3,0.0,0.0,1.1,4.0,-8.9,27.9,-0.5,0.0,7.0,-3.2,0.0,0.0,1.1,1.3,13.2,22.3,-0.5,0.0,10.9,-2.5,0.0,0.0,1.0,1.0,23.8,29.6,-0.5,-0.6,10.8,-1.7,0.0,0.0,0.8,0.9,20.1,25.1,10

# check the data
import pandas as pd
df = pd.read_csv('arrhythmia.data', header=None)

# since the data has many columns, take just the first few and name them (as per the documentation)
data = df[[0,1,2,3,4,5]]
data.columns = ['age', 'sex', 'height', 'weight', 'QRS duration', 'P-R interval']

import matplotlib.pyplot as plt
plt.rcParams['figure.figsize'] = [15, 15] # make the plot bigger so the subplots don't overlap
data.hist(); # use a semicolon to supress return value

from pandas.plotting import scatter_matrix
scatter_matrix(data);

Part 2: Using tf.keras¶

# use keras get_file to download the auto MPG dataset
# source: https://archive.ics.uci.edu/ml/datasets/Auto+MPG
#url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data'

### alternate URL
url = 'https://raw.githubusercontent.com/lazyprogrammer/machine_learning_examples/master/tf2.0/auto-mpg.data'

# Install TensorFlow

import tensorflow as tf
print(tf.__version__)

2.2.0-rc2

# check out the documentation for other arguments
tf.keras.utils.get_file('auto-mpg.data', url)

Downloading data from https://raw.githubusercontent.com/lazyprogrammer/machine_learning_examples/master/tf2.0/auto-mpg.data
32768/30286 [================================] - 0s 1us/step

'/root/.keras/datasets/auto-mpg.data'

!head /root/.keras/datasets/auto-mpg.data

18.0   8   307.0      130.0      3504.      12.0   70  1    "chevrolet chevelle malibu"
15.0   8   350.0      165.0      3693.      11.5   70  1    "buick skylark 320"
18.0   8   318.0      150.0      3436.      11.0   70  1    "plymouth satellite"
16.0   8   304.0      150.0      3433.      12.0   70  1    "amc rebel sst"
17.0   8   302.0      140.0      3449.      10.5   70  1    "ford torino"
15.0   8   429.0      198.0      4341.      10.0   70  1    "ford galaxie 500"
14.0   8   454.0      220.0      4354.       9.0   70  1    "chevrolet impala"
14.0   8   440.0      215.0      4312.       8.5   70  1    "plymouth fury iii"
14.0   8   455.0      225.0      4425.      10.0   70  1    "pontiac catalina"
15.0   8   390.0      190.0      3850.       8.5   70  1    "amc ambassador dpl"

# unless you specify an alternative path, the data will go into /root/.keras/datasets/
df = pd.read_csv('/root/.keras/datasets/auto-mpg.data', header=None, delim_whitespace=True)
df.head()

	0	1	2	3	4	5	6	7	8
0	18.0	8	307.0	130.0	3504.0	12.0	70	1	chevrolet chevelle malibu
1	15.0	8	350.0	165.0	3693.0	11.5	70	1	buick skylark 320
2	18.0	8	318.0	150.0	3436.0	11.0	70	1	plymouth satellite
3	16.0	8	304.0	150.0	3433.0	12.0	70	1	amc rebel sst
4	17.0	8	302.0	140.0	3449.0	10.5	70	1	ford torino

Part 3: Upload the file yourself¶

# another method: upload your own file

##### PLEASE NOTE: IT DOES NOT MATTER WHICH FILE YOU UPLOAD
##### YOU CAN UPLOAD ANY FILE YOU WANT
##### IN FACT, YOU ARE ENCOURAGED TO EXPLORE ON YOUR OWN

# if you must, then get the file from here:
# https://raw.githubusercontent.com/lazyprogrammer/machine_learning_examples/master/tf2.0/daily-minimum-temperatures-in-me.csv

from google.colab import files
uploaded = files.upload()

 <input type="file" id="files-f85a97ca-0bfe-4c55-8369-d830289c8925" name="files[]" multiple disabled />
 <output id="result-f85a97ca-0bfe-4c55-8369-d830289c8925">
  Upload widget is only available when the cell has been executed in the
  current browser session. Please rerun this cell to enable.
  </output>
  <script src="/nbextensions/google.colab/files.js"></script>

Saving daily-minimum-temperatures-in-me.csv to daily-minimum-temperatures-in-me.csv

uploaded

{'daily-minimum-temperatures-in-me.csv': b'"Date","Daily minimum temperatures in Melbourne, Australia, 1981-1990"\r\n"1981-01-01",20.7\r\n"1981-01-02",17.9\r\n"1981-01-03",18.8\r\n"1981-01-04",14.6\r\n"1981-01-05",15.8\r\n"1981-01-06",15.8\r\n"1981-01-07",15.8\r\n"1981-01-08",17.4\r\n"1981-01-09",21.8\r\n"1981-01-10",20.0\r\n"1981-01-11",16.2\r\n"1981-01-12",13.3\r\n"1981-01-13",16.7\r\n"1981-01-14",21.5\r\n"1981-01-15",25.0\r\n"1981-01-16",20.7\r\n"1981-01-17",20.6\r\n"1981-01-18",24.8\r\n"1981-01-19",17.7\r\n"1981-01-20",15.5\r\n"1981-01-21",18.2\r\n"1981-01-22",12.1\r\n"1981-01-23",14.4\r\n"1981-01-24",16.0\r\n"1981-01-25",16.5\r\n"1981-01-26",18.7\r\n"1981-01-27",19.4\r\n"1981-01-28",17.2\r\n"1981-01-29",15.5\r\n"1981-01-30",15.1\r\n"1981-01-31",15.4\r\n"1981-02-01",15.3\r\n"1981-02-02",18.8\r\n"1981-02-03",21.9\r\n"1981-02-04",19.9\r\n"1981-02-05",16.6\r\n"1981-02-06",16.8\r\n"1981-02-07",14.6\r\n"1981-02-08",17.1\r\n"1981-02-09",25.0\r\n"1981-02-10",15.0\r\n"1981-02-11",13.7\r\n"1981-02-12",13.9\r\n"1981-02-13",18.3\r\n"1981-02-14",22.0\r\n"1981-02-15",22.1\r\n"1981-02-16",21.2\r\n"1981-02-17",18.4\r\n"1981-02-18",16.6\r\n"1981-02-19",16.1\r\n"1981-02-20",15.7\r\n"1981-02-21",16.6\r\n"1981-02-22",16.5\r\n"1981-02-23",14.4\r\n"1981-02-24",14.4\r\n"1981-02-25",18.5\r\n"1981-02-26",16.9\r\n"1981-02-27",17.5\r\n"1981-02-28",21.2\r\n"1981-03-01",17.8\r\n"1981-03-02",18.6\r\n"1981-03-03",17.0\r\n"1981-03-04",16.0\r\n"1981-03-05",13.3\r\n"1981-03-06",14.3\r\n"1981-03-07",11.4\r\n"1981-03-08",16.3\r\n"1981-03-09",16.1\r\n"1981-03-10",11.8\r\n"1981-03-11",12.2\r\n"1981-03-12",14.7\r\n"1981-03-13",11.8\r\n"1981-03-14",11.3\r\n"1981-03-15",10.6\r\n"1981-03-16",11.7\r\n"1981-03-17",14.2\r\n"1981-03-18",11.2\r\n"1981-03-19",16.9\r\n"1981-03-20",16.7\r\n"1981-03-21",8.1\r\n"1981-03-22",8.0\r\n"1981-03-23",8.8\r\n"1981-03-24",13.4\r\n"1981-03-25",10.9\r\n"1981-03-26",13.4\r\n"1981-03-27",11.0\r\n"1981-03-28",15.0\r\n"1981-03-29",15.7\r\n"1981-03-30",14.5\r\n"1981-03-31",15.8\r\n"1981-04-01",16.7\r\n"1981-04-02",16.8\r\n"1981-04-03",17.5\r\n"1981-04-04",17.1\r\n"1981-04-05",18.1\r\n"1981-04-06",16.6\r\n"1981-04-07",10.0\r\n"1981-04-08",14.9\r\n"1981-04-09",15.9\r\n"1981-04-10",13.0\r\n"1981-04-11",7.6\r\n"1981-04-12",11.5\r\n"1981-04-13",13.5\r\n"1981-04-14",13.0\r\n"1981-04-15",13.3\r\n"1981-04-16",12.1\r\n"1981-04-17",12.4\r\n"1981-04-18",13.2\r\n"1981-04-19",13.8\r\n"1981-04-20",10.6\r\n"1981-04-21",9.0\r\n"1981-04-22",10.0\r\n"1981-04-23",9.8\r\n"1981-04-24",11.5\r\n"1981-04-25",8.9\r\n"1981-04-26",7.4\r\n"1981-04-27",9.9\r\n"1981-04-28",9.3\r\n"1981-04-29",9.9\r\n"1981-04-30",7.4\r\n"1981-05-01",8.6\r\n"1981-05-02",11.9\r\n"1981-05-03",14.0\r\n"1981-05-04",8.6\r\n"1981-05-05",10.0\r\n"1981-05-06",13.5\r\n"1981-05-07",12.0\r\n"1981-05-08",10.5\r\n"1981-05-09",10.7\r\n"1981-05-10",8.1\r\n"1981-05-11",10.1\r\n"1981-05-12",10.6\r\n"1981-05-13",5.3\r\n"1981-05-14",6.6\r\n"1981-05-15",8.5\r\n"1981-05-16",11.2\r\n"1981-05-17",9.8\r\n"1981-05-18",5.9\r\n"1981-05-19",3.2\r\n"1981-05-20",2.1\r\n"1981-05-21",3.4\r\n"1981-05-22",5.4\r\n"1981-05-23",9.6\r\n"1981-05-24",11.5\r\n"1981-05-25",12.3\r\n"1981-05-26",12.6\r\n"1981-05-27",11.0\r\n"1981-05-28",11.2\r\n"1981-05-29",11.4\r\n"1981-05-30",11.8\r\n"1981-05-31",12.8\r\n"1981-06-01",11.6\r\n"1981-06-02",10.6\r\n"1981-06-03",9.8\r\n"1981-06-04",11.2\r\n"1981-06-05",5.7\r\n"1981-06-06",7.1\r\n"1981-06-07",2.5\r\n"1981-06-08",3.5\r\n"1981-06-09",4.6\r\n"1981-06-10",11.0\r\n"1981-06-11",5.7\r\n"1981-06-12",7.7\r\n"1981-06-13",10.4\r\n"1981-06-14",11.4\r\n"1981-06-15",9.2\r\n"1981-06-16",6.1\r\n"1981-06-17",2.7\r\n"1981-06-18",4.3\r\n"1981-06-19",6.3\r\n"1981-06-20",3.8\r\n"1981-06-21",4.4\r\n"1981-06-22",7.1\r\n"1981-06-23",4.8\r\n"1981-06-24",5.8\r\n"1981-06-25",6.2\r\n"1981-06-26",7.3\r\n"1981-06-27",9.2\r\n"1981-06-28",10.2\r\n"1981-06-29",9.5\r\n"1981-06-30",9.5\r\n"1981-07-01",10.7\r\n"1981-07-02",10.0\r\n"1981-07-03",6.5\r\n"1981-07-04",7.0\r\n"1981-07-05",7.4\r\n"1981-07-06",8.1\r\n"1981-07-07",6.6\r\n"1981-07-08",8.3\r\n"1981-07-09",8.9\r\n"1981-07-10",4.6\r\n"1981-07-11",6.8\r\n"1981-07-12",5.7\r\n"1981-07-13",6.1\r\n"1981-07-14",7.0\r\n"1981-07-15",7.2\r\n"1981-07-16",6.3\r\n"1981-07-17",8.8\r\n"1981-07-18",5.0\r\n"1981-07-19",7.4\r\n"1981-07-20",10.1\r\n"1981-07-21",12.0\r\n"1981-07-22",9.0\r\n"1981-07-23",8.9\r\n"1981-07-24",9.8\r\n"1981-07-25",9.0\r\n"1981-07-26",9.2\r\n"1981-07-27",7.7\r\n"1981-07-28",8.0\r\n"1981-07-29",6.1\r\n"1981-07-30",3.5\r\n"1981-07-31",3.2\r\n"1981-08-01",5.7\r\n"1981-08-02",7.7\r\n"1981-08-03",9.0\r\n"1981-08-04",10.0\r\n"1981-08-05",6.2\r\n"1981-08-06",6.9\r\n"1981-08-07",6.5\r\n"1981-08-08",6.8\r\n"1981-08-09",7.0\r\n"1981-08-10",5.2\r\n"1981-08-11",3.0\r\n"1981-08-12",5.6\r\n"1981-08-13",7.9\r\n"1981-08-14",9.0\r\n"1981-08-15",8.6\r\n"1981-08-16",10.3\r\n"1981-08-17",10.5\r\n"1981-08-18",7.6\r\n"1981-08-19",9.7\r\n"1981-08-20",12.5\r\n"1981-08-21",7.4\r\n"1981-08-22",7.9\r\n"1981-08-23",3.9\r\n"1981-08-24",6.6\r\n"1981-08-25",4.6\r\n"1981-08-26",7.0\r\n"1981-08-27",6.0\r\n"1981-08-28",5.5\r\n"1981-08-29",8.1\r\n"1981-08-30",5.5\r\n"1981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"1990-04-21",14.5\r\n"1990-04-22",14.7\r\n"1990-04-23",11.2\r\n"1990-04-24",12.7\r\n"1990-04-25",13.7\r\n"1990-04-26",11.5\r\n"1990-04-27",10.4\r\n"1990-04-28",8.9\r\n"1990-04-29",11.1\r\n"1990-04-30",9.5\r\n"1990-05-01",13.0\r\n"1990-05-02",13.9\r\n"1990-05-03",12.6\r\n"1990-05-04",14.3\r\n"1990-05-05",16.0\r\n"1990-05-06",13.3\r\n"1990-05-07",7.0\r\n"1990-05-08",4.9\r\n"1990-05-09",6.9\r\n"1990-05-10",13.7\r\n"1990-05-11",10.6\r\n"1990-05-12",12.3\r\n"1990-05-13",11.1\r\n"1990-05-14",10.2\r\n"1990-05-15",9.5\r\n"1990-05-16",8.9\r\n"1990-05-17",13.4\r\n"1990-05-18",9.1\r\n"1990-05-19",9.4\r\n"1990-05-20",8.7\r\n"1990-05-21",5.8\r\n"1990-05-22",4.5\r\n"1990-05-23",7.2\r\n"1990-05-24",10.0\r\n"1990-05-25",10.5\r\n"1990-05-26",10.7\r\n"1990-05-27",8.2\r\n"1990-05-28",6.1\r\n"1990-05-29",4.5\r\n"1990-05-30",6.1\r\n"1990-05-31",9.8\r\n"1990-06-01",9.7\r\n"1990-06-02",8.2\r\n"1990-06-03",8.4\r\n"1990-06-04",8.5\r\n"1990-06-05",10.4\r\n"1990-06-06",6.8\r\n"1990-06-07",6.0\r\n"1990-06-08",6.6\r\n"1990-06-09",7.8\r\n"1990-06-10",10.3\r\n"1990-06-11",7.2\r\n"1990-06-12",7.4\r\n"1990-06-13",11.4\r\n"1990-06-14",5.4\r\n"1990-06-15",4.4\r\n"1990-06-16",6.4\r\n"1990-06-17",9.3\r\n"1990-06-18",7.7\r\n"1990-06-19",8.1\r\n"1990-06-20",8.3\r\n"1990-06-21",9.1\r\n"1990-06-22",7.7\r\n"1990-06-23",10.6\r\n"1990-06-24",8.2\r\n"1990-06-25",7.9\r\n"1990-06-26",5.2\r\n"1990-06-27",5.9\r\n"1990-06-28",3.7\r\n"1990-06-29",5.6\r\n"1990-06-30",9.4\r\n"1990-07-01",7.4\r\n"1990-07-02",7.3\r\n"1990-07-03",7.7\r\n"1990-07-04",7.7\r\n"1990-07-05",9.3\r\n"1990-07-06",4.4\r\n"1990-07-07",5.7\r\n"1990-07-08",10.2\r\n"1990-07-09",10.2\r\n"1990-07-10",9.3\r\n"1990-07-11",5.4\r\n"1990-07-12",5.0\r\n"1990-07-13",7.6\r\n"1990-07-14",9.6\r\n"1990-07-15",10.4\r\n"1990-07-16",11.2\r\n"1990-07-17",9.1\r\n"1990-07-18",11.2\r\n"1990-07-19",6.8\r\n"1990-07-20",8.3\r\n"1990-07-21",9.7\r\n"1990-07-22",9.6\r\n"1990-07-23",9.8\r\n"1990-07-24",10.8\r\n"1990-07-25",9.2\r\n"1990-07-26",6.5\r\n"1990-07-27",8.1\r\n"1990-07-28",7.3\r\n"1990-07-29",7.9\r\n"1990-07-30",6.0\r\n"1990-07-31",5.0\r\n"1990-08-01",6.8\r\n"1990-08-02",9.8\r\n"1990-08-03",5.7\r\n"1990-08-04",8.6\r\n"1990-08-05",10.6\r\n"1990-08-06",7.8\r\n"1990-08-07",7.7\r\n"1990-08-08",8.6\r\n"1990-08-09",6.5\r\n"1990-08-10",6.9\r\n"1990-08-11",6.4\r\n"1990-08-12",8.5\r\n"1990-08-13",7.8\r\n"1990-08-14",9.3\r\n"1990-08-15",8.4\r\n"1990-08-16",7.8\r\n"1990-08-17",7.4\r\n"1990-08-18",7.7\r\n"1990-08-19",8.9\r\n"1990-08-20",9.7\r\n"1990-08-21",9.9\r\n"1990-08-22",6.1\r\n"1990-08-23",6.6\r\n"1990-08-24",7.6\r\n"1990-08-25",7.4\r\n"1990-08-26",8.0\r\n"1990-08-27",2.1\r\n"1990-08-28",5.9\r\n"1990-08-29",11.6\r\n"1990-08-30",8.6\r\n"1990-08-31",7.9\r\n"1990-09-01",6.0\r\n"1990-09-02",9.5\r\n"1990-09-03",8.6\r\n"1990-09-04",7.6\r\n"1990-09-05",10.4\r\n"1990-09-06",10.3\r\n"1990-09-07",7.5\r\n"1990-09-08",3.0\r\n"1990-09-09",5.3\r\n"1990-09-10",10.5\r\n"1990-09-11",14.6\r\n"1990-09-12",12.6\r\n"1990-09-13",9.8\r\n"1990-09-14",7.2\r\n"1990-09-15",10.1\r\n"1990-09-16",10.4\r\n"1990-09-17",3.7\r\n"1990-09-18",7.3\r\n"1990-09-19",11.6\r\n"1990-09-20",16.3\r\n"1990-09-21",9.6\r\n"1990-09-22",6.8\r\n"1990-09-23",5.2\r\n"1990-09-24",10.6\r\n"1990-09-25",16.3\r\n"1990-09-26",9.8\r\n"1990-09-27",4.6\r\n"1990-09-28",11.1\r\n"1990-09-29",8.7\r\n"1990-09-30",10.0\r\n"1990-10-01",11.3\r\n"1990-10-02",10.5\r\n"1990-10-03",9.9\r\n"1990-10-04",11.0\r\n"1990-10-05",14.0\r\n"1990-10-06",9.2\r\n"1990-10-07",9.8\r\n"1990-10-08",6.0\r\n"1990-10-09",9.8\r\n"1990-10-10",9.2\r\n"1990-10-11",11.8\r\n"1990-10-12",10.3\r\n"1990-10-13",7.5\r\n"1990-10-14",7.7\r\n"1990-10-15",15.8\r\n"1990-10-16",14.6\r\n"1990-10-17",10.5\r\n"1990-10-18",11.3\r\n"1990-10-19",10.9\r\n"1990-10-20",6.4\r\n"1990-10-21",10.9\r\n"1990-10-22",9.0\r\n"1990-10-23",10.9\r\n"1990-10-24",12.4\r\n"1990-10-25",11.6\r\n"1990-10-26",13.3\r\n"1990-10-27",14.4\r\n"1990-10-28",18.4\r\n"1990-10-29",13.6\r\n"1990-10-30",14.9\r\n"1990-10-31",14.8\r\n"1990-11-01",15.4\r\n"1990-11-02",11.8\r\n"1990-11-03",13.0\r\n"1990-11-04",11.1\r\n"1990-11-05",12.5\r\n"1990-11-06",18.3\r\n"1990-11-07",19.2\r\n"1990-11-08",15.4\r\n"1990-11-09",13.1\r\n"1990-11-10",11.5\r\n"1990-11-11",8.6\r\n"1990-11-12",12.6\r\n"1990-11-13",13.8\r\n"1990-11-14",14.6\r\n"1990-11-15",13.2\r\n"1990-11-16",12.3\r\n"1990-11-17",8.8\r\n"1990-11-18",10.7\r\n"1990-11-19",9.9\r\n"1990-11-20",8.3\r\n"1990-11-21",15.0\r\n"1990-11-22",12.2\r\n"1990-11-23",10.5\r\n"1990-11-24",11.1\r\n"1990-11-25",13.0\r\n"1990-11-26",12.9\r\n"1990-11-27",8.8\r\n"1990-11-28",14.7\r\n"1990-11-29",14.7\r\n"1990-11-30",12.7\r\n"1990-12-01",13.3\r\n"1990-12-02",13.2\r\n"1990-12-03",16.2\r\n"1990-12-04",17.3\r\n"1990-12-05",20.5\r\n"1990-12-06",20.2\r\n"1990-12-07",19.4\r\n"1990-12-08",15.5\r\n"1990-12-09",14.1\r\n"1990-12-10",11.0\r\n"1990-12-11",11.1\r\n"1990-12-12",14.0\r\n"1990-12-13",11.4\r\n"1990-12-14",12.5\r\n"1990-12-15",13.4\r\n"1990-12-16",13.6\r\n"1990-12-17",13.9\r\n"1990-12-18",17.2\r\n"1990-12-19",14.7\r\n"1990-12-20",15.4\r\n"1990-12-21",13.1\r\n"1990-12-22",13.2\r\n"1990-12-23",13.9\r\n"1990-12-24",10.0\r\n"1990-12-25",12.9\r\n"1990-12-26",14.6\r\n"1990-12-27",14.0\r\n"1990-12-28",13.6\r\n"1990-12-29",13.5\r\n"1990-12-30",15.7\r\n"1990-12-31",13.0\r\n\r\nDaily minimum temperatures in Melbourne, Australia, 1981-1990\r\n\r\n'}

# file is uploaded to the current directory
!ls

arrhythmia.data  daily-minimum-temperatures-in-me.csv  sample_data

# open the file
# the last few lines are junk
df = pd.read_csv('daily-minimum-temperatures-in-me.csv', error_bad_lines=False)
df.head()

b'Skipping line 3653: expected 2 fields, saw 3\n'

	Date	Daily minimum temperatures in Melbourne, Australia, 1981-1990
0	1981-01-01	20.7
1	1981-01-02	17.9
2	1981-01-03	18.8
3	1981-01-04	14.6
4	1981-01-05	15.8

# upload a Python file with some useful functions (meant for fake_util.py)
from google.colab import files
uploaded = files.upload()

 <input type="file" id="files-c590b543-ffcc-4177-91d3-62725b363169" name="files[]" multiple disabled />
 <output id="result-c590b543-ffcc-4177-91d3-62725b363169">
  Upload widget is only available when the cell has been executed in the
  current browser session. Please rerun this cell to enable.
  </output>
  <script src="/nbextensions/google.colab/files.js"></script>

Saving fake_util.py to fake_util.py

from fake_util import my_useful_function
my_useful_function()

hello world

!pwd

/content

Part 4: Access files from Google Drive¶

# Access files from your Google Drive
from google.colab import drive
drive.mount('/content/gdrive')

# Check current directory - now gdrive is there
!ls

# What's in gdrive?
!ls gdrive

# Whoa! Look at all this great VIP content!
!ls '/content/gdrive/My Drive/'

Copyright Qalmaqihir For more information, visit us at www.github.com/qalmaqihir/