Ci-dessous, les différences entre deux révisions de la page.
Les deux révisions précédentes Révision précédente Prochaine révision | Révision précédente Prochaine révision Les deux révisions suivantes | ||
python:first_course_statistics [2016/10/13 12:52] Beretta, Anna Letizia |
python:first_course_statistics [2016/10/24 14:29] Beretta, Anna Letizia |
||
---|---|---|---|
Ligne 13: | Ligne 13: | ||
===== Histogram (p.5) ===== | ===== Histogram (p.5) ===== | ||
- | |||
- | FB: this script works fine ! Do not delete it ! | ||
<code python> | <code python> | ||
Ligne 37: | Ligne 35: | ||
import matplotlib.pyplot as plt | import matplotlib.pyplot as plt | ||
import pandas as pd | import pandas as pd | ||
- | gysr1_boxplot = pd.read_csv('D:\Python\Libri\A Casebook for a First Course in Statistics and Data Analysis Datasets\Data\Tab\geyser1.TAB', '\t') | + | gysr1_boxplot = pd.read_csv('...\geyser1.TAB', '\t') |
data_gysr1 = gysr1_boxplot['Interval'] | data_gysr1 = gysr1_boxplot['Interval'] | ||
plt.boxplot(data_gysr1) | plt.boxplot(data_gysr1) | ||
Ligne 52: | Ligne 50: | ||
===== ScatterPlot (p. 7) ===== | ===== ScatterPlot (p. 7) ===== | ||
- | AB: Put face- and edgecolor to change both of them. You can also have to different color for the in- and outside of each point. | + | AB: Put face- and edgecolor to change both of them. You can also have two different colors for the in- and outside of each dot. |
<code python> | <code python> | ||
import matplotlib.pyplot as plt | import matplotlib.pyplot as plt | ||
import pandas as pd | import pandas as pd | ||
- | geysr1_scatterplot = pd.read_csv('D:\Python\Libri\A Casebook for a First Course in Statistics and Data Analysis Datasets\Data\Tab\geyser1.TAB', '\t') | + | geysr1_scatterplot = pd.read_csv('...\geyser1.TAB', '\t') |
geysr1_data_Xax = geysr1_scatterplot['Duration'] | geysr1_data_Xax = geysr1_scatterplot['Duration'] | ||
geysr1_data_Yax = geysr1_scatterplot['Interval'] | geysr1_data_Yax = geysr1_scatterplot['Interval'] | ||
Ligne 67: | Ligne 65: | ||
plt.show() | plt.show() | ||
</code> | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | ===== Descriptive statistics (p.9) ===== | ||
+ | |||
+ | Note: try different examples, e.g. the whole population or only those where 'Duration' <= 3, the whole dataframe | ||
+ | |||
+ | [[http://pandas.pydata.org/pandas-docs/stable/basics.html#descriptive-statistics|doc]] – [[http://www.marsja.se/pandas-python-descriptive-statistics/|example]] | ||
+ | |||
+ | <code python> | ||
+ | import pandas as pd | ||
+ | gysr1 = pd.read_csv('../geyser1.tab', '\t') | ||
+ | gysr1['Duration'][gysr1['Duration'] <= 3].describe() | ||
+ | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | ===== Boxplot (p.9) ===== | ||
+ | |||
+ | Selecting rows in a dataframe: [[http://pandas.pydata.org/pandas-docs/stable/indexing.html#the-where-method-and-masking|doc]] / [[http://stackoverflow.com/questions/17071871/select-rows-from-a-dataframe-based-on-values-in-a-column-in-pandas|example]] | ||
+ | |||
+ | <code python> | ||
+ | import matplotlib.pyplot as plt | ||
+ | import pandas as pd | ||
+ | gysr1 = pd.read_csv('../geyser1.tab', '\t') | ||
+ | gysr1_inf3 = gysr1.loc[gysr1['Duration'] <= 3] | ||
+ | gysr1_sup3 = gysr1.loc[gysr1['Duration'] > 3] | ||
+ | plt.boxplot([gysr1_inf3['Interval'],gysr1_sup3['Interval']], labels= ['inf3','sup3']) | ||
+ | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
====== International adoption rates (p.13) ====== | ====== International adoption rates (p.13) ====== | ||
+ | |||
+ | ===== Boxplot (p.14) ===== | ||
+ | |||
+ | <code python> | ||
+ | import matplotlib.pyplot as plt | ||
+ | import pandas as pd | ||
+ | adopt_data = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\\adopt.TAB', '\t') | ||
+ | adopt1 = adopt_data['Visa91'] | ||
+ | plt.boxplot(adopt1) | ||
+ | ax = plt.gca() | ||
+ | ax.set_title('Box and Whisker Plot') | ||
+ | ax.set_xlabel('39 cases') | ||
+ | ax.set_ylabel('Number of visas in 1991') | ||
+ | plt.show() | ||
+ | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | ===== Histogram (p.14) ===== | ||
+ | |||
+ | <code python> | ||
+ | import matplotlib.pyplot as plt | ||
+ | import pandas as pd | ||
+ | adopt_data = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\\adopt.TAB', '\t') | ||
+ | adopt1 = adopt_data['Visa91'] | ||
+ | plt.hist(adopt1) | ||
+ | plt.show() | ||
+ | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | =====Scatterplot (p. 17)===== | ||
+ | <code python> | ||
+ | import matplotlib.pyplot as plt | ||
+ | import pandas as pd | ||
+ | adoption_scatterplot = pd.read_csv('...\adopt.TAB', '\t') | ||
+ | adopt_data_Xax = adoption_scatterplot['Visa88'] | ||
+ | adopt_data_Yax = adoption_scatterplot['Visa91'] | ||
+ | plt.scatter(adopt_data_Xax, adopt_data_Yax, facecolor='y', edgecolor='y') | ||
+ | ax = plt.gca() | ||
+ | ax.set_xlabel('Number of Visas in 1988') | ||
+ | ax.set_ylim([0,2700]) | ||
+ | ax.set_xlim([0,5000]) | ||
+ | ax.set_ylabel('Number of Visas in 1991') | ||
+ | ax.set_title('ScatterPlot of Visa91 vs Visa88') | ||
+ | plt.show() | ||
+ | </code> | ||
+ | |||
+ | |||
+ | \\ | ||
+ | |||
+ | |||
+ | =====Scatterplot (p.18)===== | ||
+ | import matplotlib.pyplot as plt | ||
+ | import pandas as pd | ||
+ | adoption_scatterplot = pd.read_csv('D:\Python\Libri\A_Casebook_for_a_First_Course_in_Statistics_and_Data_Analysis_Datasets\Data\Tab\\adopt.TAB', '\t') | ||
+ | adopt_data_Xax = adoption_scatterplot['Visa91'] | ||
+ | adopt_data_Yax = adoption_scatterplot['Visa92'] | ||
+ | plt.scatter(adopt_data_Xax, adopt_data_Yax, facecolor='y', edgecolor='y') | ||
+ | ax = plt.gca() | ||
+ | ax.set_xlabel('Number of Visas in 1991') | ||
+ | ax.set_ylim([0,1800]) | ||
+ | ax.set_xlim([0,2700]) | ||
+ | ax.set_ylabel('Number of Visas in 1992') | ||
+ | ax.set_title('ScatterPlot of Visa92 vs Visa91') | ||
+ | plt.show() | ||
+ | </code> | ||
+ | |||