Différences

Ci-dessous, les différences entre deux révisions de la page.

--- python:first_course_statistics [2016/10/31 11:00] – [Scatter Plot of PRODJAPN vs QUALJAPN (p. 27)] alberetta
+++ python:first_course_statistics [2017/09/26 08:54] (Version actuelle) – [General instructions] fberetta
@@ Ligne 5: / Ligne 5: @@
   * pandas [[http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe|dataframes]]
   * [[http://matplotlib.org/api/pyplot_summary.html|matplotlib.pyplot]]
+Get the data from [[http://people.stern.nyu.edu/jsimonof/Casebook/Data/ASCII/README.html|this site]].
 Save your scripts in a folder inside the data folder, calling the script folder 'my_scripts' or whaterver. If  'my-scripts' is set as your [[python:generic_features#get_the_current_working_directory_address|current working directory]], then the data files are available under this address '../[data file]', for instantce: '../geyser1.TAB'
@@ Ligne 35: / Ligne 39: @@
 import matplotlib.pyplot as plt
 import pandas as pd
-gysr1_boxplot = pd.read_csv('...\geyser1.TAB', '\t')
+gysr1_boxplot = pd.read_csv('.../geyser1.TAB', '\t')
 data_gysr1 = gysr1_boxplot['Interval']
 plt.boxplot(data_gysr1)
@@ Ligne 55: / Ligne 59: @@
 import matplotlib.pyplot as plt
 import pandas as pd
-geysr1_scatterplot = pd.read_csv('...\geyser1.TAB', '\t')
+geysr1_scatterplot = pd.read_csv('.../geyser1.TAB', '\t')
 geysr1_data_Xax = geysr1_scatterplot['Duration']
 geysr1_data_Yax = geysr1_scatterplot['Interval']
@@ Ligne 256: / Ligne 260: @@
 </code>
+=====Scatter Plot of PRODNONJ cs QUALNONJ (p. 27)=====
+<code Python>
+import pandas as pd
+import matplotlib.pyplot as plt
+scatter_plot = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\\prdq.TAB', '\t')
+productivity_Y = scatter_plot['ProdNonJ']
+quality_X = scatter_plot['QualNonJ']
+plt.scatter(productivity_Y, quality_X, bins=20, colors='r')
+ax = plt.gca()
+ax.set_Xlabel('Assembly defects per 100 cars (non-Japanese origin)')
+ax.set_Ylabel('Hours per vehicle (non-Japanese origin')
+ax.set_title('Scatter Plot of PRODNONJ VS QUALNONJ')
+plt.show()
+</code>
+===== Scatterplot of productivity VS quality (p. 28) =====
+<code python>
+import pandas as pd
+import matplotlib.pyplot as plt
+scatter_plot = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\\prdq.TAB', '\t')
+productivity_Y = scatter_plot['Producti']
+quality_X = scatter_plot['Quality']
+plt.scatter(productivity_Y, quality_X, bins=20, colors='r')
+ax = plt.gca()
+ax.set_Xlabel('Assembly defects per 100 cars')
+ax.set_Ylabel('Hours per vehicle')
+ax.set_title('Scatter Plot of PRODUCTIVITY VS QUALITY')
+plt.show()
+</code>
+===== Productivity versus quality in the assembly plant (p.29) =====
+It worked the first time but now it doesn't work again. Maybe again a windows error?
+<code python>
+#1
+import matplotlib.pyplot as plt
+import pandas as pd
+data_comparison = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\prdq.TAB', '\t')
+non_japanese = data_comparison.loc[data_comparison['QualNonJ']]
+japanese = data_comparison.loc[data_comparison['QualJapn']]
+plt.boxplot([non_japanese['Quality'],japanese['Quality']], labels= ['Non-japanese','Japanese'])
+plt.show()
+#2
+import matplotlib.pyplot as plt
+import pandas as pd
+data_comparison = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\prdq.TAB', '\t')
+non_japanese = data_comparison.loc[data_comparison['ProdNonJ']]
+japanese = data_comparison.loc[data_comparison['ProdJapn']]
+plt.boxplot([non_japanese['Producti'],japanese['Producti']], labels= ['Non-japanese','Japanese'])
+plt.show()
+</code>