Poterek

setosa.csv

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+Sepal.Length,Sepal.Width,Petal.Length,Petal.Width,Species
+5.1,3.5,1.4,0.2,setosa
+4.9,3.0,1.4,0.2,setosa
+4.7,3.2,1.3,0.2,setosa
+4.6,3.1,1.5,0.2,setosa
+5.0,3.6,1.4,0.2,setosa
+5.4,3.9,1.7,0.4,setosa
+4.6,3.4,1.4,0.3,setosa
+5.0,3.4,1.5,0.2,setosa
+4.4,2.9,1.4,0.2,setosa
+4.9,3.1,1.5,0.1,setosa
+5.4,3.7,1.5,0.2,setosa
+4.8,3.4,1.6,0.2,setosa
+4.8,3.0,1.4,0.1,setosa
+4.3,3.0,1.1,0.1,setosa
+5.8,4.0,1.2,0.2,setosa
+5.7,4.4,1.5,0.4,setosa
+5.4,3.9,1.3,0.4,setosa
+5.1,3.5,1.4,0.3,setosa
+5.7,3.8,1.7,0.3,setosa
+5.1,3.8,1.5,0.3,setosa
+5.4,3.4,1.7,0.2,setosa
+5.1,3.7,1.5,0.4,setosa
+4.6,3.6,1.0,0.2,setosa
+5.1,3.3,1.7,0.5,setosa
+4.8,3.4,1.9,0.2,setosa
+5.0,3.0,1.6,0.2,setosa
+5.0,3.4,1.6,0.4,setosa
+5.2,3.5,1.5,0.2,setosa
+5.2,3.4,1.4,0.2,setosa
+4.7,3.2,1.6,0.2,setosa
+4.8,3.1,1.6,0.2,setosa
+5.4,3.4,1.5,0.4,setosa
+5.2,4.1,1.5,0.1,setosa
+5.5,4.2,1.4,0.2,setosa
+4.9,3.1,1.5,0.2,setosa
+5.0,3.2,1.2,0.2,setosa
+5.5,3.5,1.3,0.2,setosa
+4.9,3.6,1.4,0.1,setosa
+4.4,3.0,1.3,0.2,setosa
+5.1,3.4,1.5,0.2,setosa
+5.0,3.5,1.3,0.3,setosa
+4.5,2.3,1.3,0.3,setosa
+4.4,3.2,1.3,0.2,setosa
+5.0,3.5,1.6,0.6,setosa
+5.1,3.8,1.9,0.4,setosa
+4.8,3.0,1.4,0.3,setosa
+5.1,3.8,1.6,0.2,setosa
+4.6,3.2,1.4,0.2,setosa
+5.3,3.7,1.5,0.2,setosa
+5.0,3.3,1.4,0.2,setosa

solution_1.py

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+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Oct 11 10:05:39 2018
+
+@author: mlpoterek
+"""
+
+def head (str, n) :
+    with open (str) as my_file:
+        first_lines = [next(my_file) for x in xrange(n)]        
+    print(first_lines)
+
+head("iris.csv", 2) #to call function with n=2

solution_2.py

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+#!/usr/bin/env python2
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Oct 11 13:09:43 2018
+
+@author: mlpoterek
+"""
+
+from pandas import DataFrame, read_csv
+import pandas as pd
+
+location = r'/Users/mlpoterek/Biocomp/IBC_EX6/iris.csv'
+df = pd.read_csv(location)
+
+#Print the last 2 rows in the last 2 columns
+last_rows = df.tail(2)
+last_cols = last_rows[['Petal.Width', 'Species']]
+print(last_cols)
+
+#Number of observations of each species
+spec_count = df['Species'].value_counts()
+print(spec_count)
+
+#Rows with Sepal.Width > 3.5
+sepal_rows = df[df['Sepal.Width'] > 3.5]
+print(sepal_rows)
+
+#Write the data for the species setosa to a csv file 'setosa.csv'
+setosa_rows = df[df['Species']=='setosa']
+setosa_rows.to_csv("setosa.csv",sep = ',', index = False)
+
+#Mean, min, and max of 'Petal.Length' for observations from virginica
+virginica_rows = df[df['Species']=='virginica']
+v_mean = virginica_rows['Petal.Length'].mean()
+v_min = virginica_rows['Petal.Length'].min()
+v_max = virginica_rows['Petal.Length'].max()
+print(v_mean, v_min, v_max)