In [10]:
import pandas
In [2]:
type(pandas)
Out[2]:
module
In [8]:
def fahr_to_celsius(temp_fahr):
    """Convert Fahrenheit to Celsius
    
    Return Celsius conversion of input"""
    temp_celsius = (temp_fahr - 32) * 5 / 9
    return temp_celsius
In [4]:
fahr_to_celsius?
In [6]:
data = pandas.read_csv("data/A1_mosquito_data.csv")
In [7]:
data.head()
Out[7]:
year temperature rainfall mosquitos
0 2001 80 157 150
1 2002 85 252 217
2 2003 86 154 153
3 2004 87 159 158
4 2005 74 292 243
  • since we have one row per year, let's set that to the index using .set_index()
In [8]:
data = data.set_index("year")
  • let's use the fahr_to_celsius() function to convert our fahr temp to celsisus on the fly (not saved)
In [9]:
fahr_to_celsius(data["temperature"])
Out[9]:
year
2001    26.666667
2002    29.444444
2003    30.000000
2004    30.555556
2005    23.333333
2006    23.888889
2007    26.666667
2008    29.444444
2009    23.333333
2010    23.333333
Name: temperature, dtype: float64
  • in pandas one way to add a column is to assign our result to a new column using the bracket structure
In [10]:
data["temperature_C"] = fahr_to_celsius(data["temperature"])
In [11]:
data.head()
Out[11]:
temperature rainfall mosquitos temperature_C
year
2001 80 157 150 26.666667
2002 85 252 217 29.444444
2003 86 154 153 30.000000
2004 87 159 158 30.555556
2005 74 292 243 23.333333
  • we can now do some graphing
In [14]:
%matplotlib inline
In [11]:
import matplotlib.pyplot as plt
In [15]:
plt.plot?
In [16]:
plt.plot(data["temperature_C"], data["mosquitos"], ".")
plt.savefig("A1_mosquito_data_mosquitos_vs_tempC.png")
In [17]:
!ls *png

A1_mosquito_data_mosquitos_vs_tempC.png
In [ ]:
In [2]:
!ls *csv

A1_mosquito_data.csv   A2_mosquito_data_C.csv B1_mosquito_data.csv
A2_mosquito_data.csv   A3_mosquito_data.csv   B2_mosquito_data.csv
  • let's start thinking about building a function.
  • we can do better on the file name of the png
  • we want it associated with the file it comes from
In [20]:
a = "A2_mosquito_data.csv" #name of file we are plotting
  • use the subset to grab 'A2_mosquito_data.' and add 'png' to it.
In [22]:
a[0:-3]  + "png"
Out[22]:
'A2_mosquito_data.png'
In [24]:
a[0:-4] + "_mosquitos_vs_tempC.png"
Out[24]:
'A2_mosquito_data_mosquitos_vs_tempC.png'
  • we can use replace() to replace substring matches
In [25]:
a.replace(".csv", ".png")
Out[25]:
'A2_mosquito_data.png'

Let's take all the above and make a function.

Function does:

  1. load data
  2. convert celsius
  3. create the plot
  4. save the plot to file
In [12]:
def create_mosquitos_vs_tempC_plot(filename):
    # write processing here
    # load data
    print("Loading", filename)
    mosquitos_data = pandas.read_csv(filename)
    # convert celsius
    mosquitos_data["temperature_C"] = fahr_to_celsius(mosquitos_data["temperature"])
    # create the plot
    print("Plotting", filename)
    plt.plot(mosquitos_data["temperature_C"], mosquitos_data["mosquitos"], ".")
    # save the plot
    filename_png = filename[0:-4] + "_mosquitos_vs_tempC.png"
    plt.savefig(filename_png)
    print("Saving", filename_png)
    return filename_png
In [15]:
name_of_png = create_mosquitos_vs_tempC_plot("A2_mosquito_data.csv")

Loading A2_mosquito_data.csv
Plotting A2_mosquito_data.csv
Saving A2_mosquito_data_mosquitos_vs_tempC.png
In [16]:
print(name_of_png)
!ls data/

A2_mosquito_data_mosquitos_vs_tempC.png
A1_mosquito_data.csv                    B1_mosquito_data.csv
A2_mosquito_data.csv                    B1_mosquito_data_mosquitos_vs_tempC.png
A2_mosquito_data_mosquitos_vs_tempC.png B2_mosquito_data.csv
A3_mosquito_data.csv                    decision_tree_example.url
In [17]:
create_mosquitos_vs_tempC_plot("B1_mosquito_data.csv")

Loading B1_mosquito_data.csv
Plotting B1_mosquito_data.csv
Saving B1_mosquito_data_mosquitos_vs_tempC.png
Out[17]:
'B1_mosquito_data_mosquitos_vs_tempC.png'
In [19]:
!ls *png

A1_mosquito_data_mosquitos_vs_tempC.png B1_mosquito_data_mosquitos_vs_tempC.png
A2_mosquito_data_mosquitos_vs_tempC.png
  • let's alter the return statement to return the data
  • then we can write it out
In [25]:
def create_mosquitos_vs_tempC_plot(filename):
    # write processing here
    # load data
    print("Loading", filename)
    mosquitos_data = pandas.read_csv(filename)
    # convert celsius
    mosquitos_data["temperature_C"] = fahr_to_celsius(mosquitos_data["temperature"])
    # create the plot
    print("Plotting", filename)
    plt.plot(mosquitos_data["temperature_C"], mosquitos_data["mosquitos"], ".")
    # save the plot
    filename_png = filename[0:-4] + "_mosquitos_vs_tempC.png"
    plt.savefig(filename_png)
    print("Saving", filename_png)
    return mosquitos_data
In [26]:
mosquito_data_A2 = create_mosquitos_vs_tempC_plot("A2_mosquito_data.csv")

Loading A2_mosquito_data.csv
Plotting A2_mosquito_data.csv
Saving A2_mosquito_data_mosquitos_vs_tempC.png
In [27]:
mosquito_data_A2.to_csv("A2_mosquito_data_C.csv")
In [30]:
mosquito_data_A2.head(6)
Out[30]:
year temperature rainfall mosquitos temperature_C
0 1960 82 200 180 27.777778
1 1961 70 227 194 21.111111
2 1962 89 231 207 31.666667
3 1963 74 114 121 23.333333
4 1964 78 147 140 25.555556
5 1965 85 151 148 29.444444
In [29]:
!head A2_mosquito_data_C.csv

,year,temperature,rainfall,mosquitos,temperature_C
0,1960,82,200,180,27.77777777777778
1,1961,70,227,194,21.11111111111111
2,1962,89,231,207,31.666666666666668
3,1963,74,114,121,23.333333333333332
4,1964,78,147,140,25.555555555555557
5,1965,85,151,148,29.444444444444443
6,1966,86,172,162,30.0
7,1967,75,106,112,23.88888888888889
8,1968,70,276,230,21.11111111111111
In [31]:
mosquito_data_A2.to_csv("A2_mosquito_data_C.csv", index=False)
In [32]:
!head A2_mosquito_data_C.csv

year,temperature,rainfall,mosquitos,temperature_C
1960,82,200,180,27.77777777777778
1961,70,227,194,21.11111111111111
1962,89,231,207,31.666666666666668
1963,74,114,121,23.333333333333332
1964,78,147,140,25.555555555555557
1965,85,151,148,29.444444444444443
1966,86,172,162,30.0
1967,75,106,112,23.88888888888889
1968,70,276,230,21.11111111111111

Let's make a python module!

  • What's a python module??
  • Python module is simply a Python source file, which can expose classes, functions and global variables
  • It's a python file .py with functions, etc.
  • Let's take our existing functions and make a module (a file).
In [43]:
!pwd

/Users/jtdennis/Desktop/python-pandas

Open up text editor:

  1. On mac, use nano from command line (navigate to desktop folder containing your notebook and data)
  2. On windows, use notepad.

import pandas import matplotlib.pyplot as plt

def fahr_to_celsius(temp_fahr): """Convert Fahrenheit to Celsius

Return Celsius conversion of input"""
temp_celsius = (temp_fahr - 32) * 5 / 9
return temp_celsius

def create_mosquitos_vs_tempC_plot(filename): """Create a png plot of mosquitos vs temp C

Parameters
----------
filename : string
    name of csv data file
Returns
-------
mosquito_data : DataFrame
    Table with temp C column
"""
# write processing here
# load data
print("Loading", filename)
mosquitos_data = pandas.read_csv(filename)
# convert celsius
mosquitos_data["temperature_C"] = fahr_to_celsius(mosquitos_data["temperature"])
# create the plot
print("Plotting", filename)
plt.plot(mosquitos_data["temperature_C"], mosquitos_data["mosquitos"], ".")
# save the plot
filename_png = filename[0:-4] + "_mosquitos_vs_tempC.png"
plt.savefig(filename_png)
print("Saving", filename_png)
return mosquitos_data
In [35]:
!cat analyze_mosquitos.py

import pandas
import matplotlib.pyplot as plt

def fahr_to_celsius(temp_fahr):
    """Convert Fahrenheit to Celsius
    
    Return Celsius conversion of input"""
    temp_celsius = (temp_fahr - 32) * 5 / 9
    return temp_celsius

def create_mosquitos_vs_tempC_plot(filename):
    '''Create a png plot of mosquitos vs temp C

    Parameters
    ----------
    filename : string
        name of csv data file
    Returns
    -------
    mosquito_data : DataFrame
        Table with temp C column
    '''
    # write processing here
    # load data
    print("Loading", filename)
    mosquitos_data = pandas.read_csv(filename)
    # convert celsius
    mosquitos_data["temperature_C"] = fahr_to_celsius(mosquitos_data["temperature"])
    # create the plot
    print("Plotting", filename)
    plt.plot(mosquitos_data["temperature_C"], mosquitos_data["mosquitos"], ".")
    # save the plot
    filename_png = filename[0:-4] + "_mosquitos_vs_tempC.png"
    plt.savefig(filename_png)
    print("Saving", filename_png)
    return filename_png
In [ ]: