The errata list is a list of errors and their corrections that were found after the product was released. If the error was corrected in a later version or reprint the date of the correction will be displayed in the column titled "Date Corrected".
The following errata were submitted by our customers and approved as valid errors by the author or editor.
| Version |
Location |
Description |
Submitted By |
Date submitted |
Date corrected |
| Printed |
Page 21
code snippet |
In the code snippet on page 21, there is an extra </match_word> at the end of line 4 that generates a syntax error. (If </match_word> is removed, the code runs as desired.)
In addition, two closing parentheses are missing. The following code works:
# Print the pattern each time it is found in the string
string = "The quick brown fox jumps over the lazy dog."
string_list = string.split()
pattern = re.compile(r"(?P<match_word>The)", re.I)
print("Output #39:")
for word in string_list:
if pattern.search(word):
print("{:s}".format(pattern.search(word).group('match_word')))
|
Mike Schulte |
Oct 13, 2016 |
Mar 24, 2017 |
| Printed |
Page 22
code snippet |
In the last line of the code snippet, there are two closing parentheses missing.
|
Mike Schulte |
Oct 13, 2016 |
Mar 24, 2017 |
| Printed |
Page 36
sixth line of code snippet |
The sixth line in the code got truncated and should, I believe, read:
ordered_dict1 = sorted(dict_copy.items(), key=lambda item: item[0])
|
Mike Schulte |
Oct 14, 2016 |
Mar 24, 2017 |
| Printed |
Page 38
2nd paragraph, first for loop code snippet |
Refer to "Output #126" in printed (page 38) and "Output #129" in code snippet:
The format statement in the first for loop is missing a closing curly bracket:
print("Output #129:")
for month in y:
print("{!s".format(month))
|
Ted Ensminger |
Nov 01, 2016 |
Mar 24, 2017 |
| Printed |
Page 41
code snippet |
The code for defining the function getMean does not work unless the "else float('nan')" is on the same line as the rest of the return statement. I suspect the backslash that is generally used to indicate this was accidentally omitted.
|
Anonymous |
Oct 17, 2016 |
Mar 24, 2017 |
| Printed |
Page 43
code snippet |
The author seems to have slipped back to python 2 accidentally. The print statements are not correctly written. Code should read:
try:
result = getMean(my_list2)
except ZeroDivisionError as detail:
print("Output #142 (Error): {}".format(float('nan')))
print("Output #142 (Error): {}".format(detail))
else:
print("Output #142 (The mean is): {}".format(result))
finally:
print("Output #142 (Finally): The finally block is executed every time")
|
Anonymous |
Oct 17, 2016 |
Mar 24, 2017 |
| Printed |
Page 45
code snippet |
The print statement has Python 2 syntax, not Python 3 syntax. Should read:
print("Output # 143:")
filereader = open(input_file, 'r')
for row in filereader:
print(row.strip())
filereader.close()
|
Anonymous |
Oct 17, 2016 |
Mar 24, 2017 |
| Printed |
Page 53
last line of code snippet |
A Python 2 style print. Parentheses are needed:
print("Output #146: Output written to file")
|
Anonymous |
Oct 17, 2016 |
Mar 24, 2017 |
| Printed |
Page 97
snippet code line 8 |
The output header list column values (page 97, line 8) and the output header list column values in the snippet code file, 10csv_reader_sum...py, do not match:
print: output_header_list = ['file_name', 'total_sales', 'average_sales']
file : output_header_list = ['file_name', 'total_cost', 'average_cost']
|
Ted Ensminger |
Nov 12, 2016 |
Mar 24, 2017 |
| Printed |
Page 99
1st paragraph, code snippet |
The pandas snippet code that calculates the sum and mean statistics (page 99) contains two minor bugs that when run from the (Windows) command line will cause Python to throw a 'NameError' exception.
This is the text from the command line after running the script (I modified the script file name for my purposes):
C:\ProjectsPy\Foundations>python pandas_sum_average1.py input_files\ output_file
s\pandas_output7.csv
Traceback (most recent call last):
File "pandas_sum_average1.py", line 22, in <module>
'total_sales': total_sales,
NameError: name 'total_sales' is not defined
C:\ProjectsPy\Foundations>
This is the offending code (bugs):
total_cost = pd.DataFrame([float(str(value).strip('$').replace(',','')) \
for value in data_frame.loc[:, 'Sale Amount']]).sum()
average_cost = pd.DataFrame([float(str(value).strip('$').replace(',','')) \
for value in data_frame.loc[:, 'Sale Amount']]).mean()
data = {'file_name': os.path.basename(input_file),
'total_sales': total_sales,
'average_sales': average_sales}
To fix this snippet, rename the 'total_cost' variable to 'total_sales', and
the 'average_cost' variable to 'average_sales'.
|
Ted Ensminger |
Nov 12, 2016 |
Mar 24, 2017 |
| Printed |
Page 114
Code snippet |
The excel snippet code '4excel_value_meets_condition.py' (page 114) contains a major bug that will cause Python to throw a 'TypeError' exception.
Line 20 in the code snippet (page 114) is testing the value in the 'sale_amount' variable for a minimum value of 1400.0. The input file (spreadsheet) contains strings in the sale_amount column which is column 3. The sale amounts contain embedded dollar signs and commas.
You can't compare a string against a floating-point value (1400.0). Take note that I created the input file following the instructions on pages 102 through 103.
This is the command line output after running the script:
C:\ProjectsPy\Foundations>python 4excel_value_meets_condition.py input_files\sal
es_2013.xlsx output_files\4output.xlsx
Traceback (most recent call last):
File "4excel_value_meets_condition.py", line 36, in <module>
if sale_amount > 1400.0:
TypeError: unorderable types: str() > float()
C:\ProjectsPy\Foundations>
This is one solution to correct this problem:
sale = worksheet.cell_value(row_index, sale_amount_column_index)
sale_amount = float(str(sale).strip('$').replace(',',''))
if sale_amount > 1400.0:
This is the command line output after running the corrected script:
C:\ProjectsPy\Foundations>python 4excel_value_meets_condition.py input_files\sal
es_2013.xlsx output_files\4output.xlsx
C:\ProjectsPy\Foundations>
|
Ted Ensminger |
Nov 14, 2016 |
Mar 24, 2017 |
| Printed |
Page 116
Code snippet, Line 9 |
The pandas snippet code 'pandas_value_meets_condition.py' (page 116) contains a major bug that will cause Python to throw a 'ValueError' exception.
Line 9 in the code snippet (page 116) is testing the value in the 'sale_amount' variable for a minimum value of 1400.0. The input file (spreadsheet) contains strings in the sale_amount column which is column 3. The sale amounts contain embedded dollar signs and commas.
You can't compare a string against a floating-point value (1400.0). Take note that I created the input file following the instructions on pages 102 through 103.
This is the command line output after running the script:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition.py input_files\sales_2013.xlsx output_files\pandas_output8.xlsx
script_name: pandas_value_meets_condition.py
input_file: input_files\sales_2013.xlsx
output_file: output_files\pandas_output8.xlsx
0 $1,200.00
1 $1,425.00
2 $1,390.00
3 $1,257.00
4 $1,725.00
5 $1,995.00
Name: Sale Amount, dtype: object
Traceback (most recent call last):
File "pandas_value_meets_condition.py", line 24, in <module>
data_frame[data_frame['Sale Amount'].astype(float) > 1400.0]
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\generic.py", line 2
950, in astype
raise_on_error=raise_on_error, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2938, in astype
return self.apply('astype', dtype=dtype, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2890, in apply
applied = getattr(b, f)(**kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
434, in astype
values=values, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
477, in _astype
values = com._astype_nansafe(values.ravel(), dtype, copy=True)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\common.py", line 19
20, in _astype_nansafe
return arr.astype(dtype)
ValueError: could not convert string to float: '$1,995.00'
C:\ProjectsPy\Foundations>
This is one solution to correct this problem:
data_frame['Sale Amount'] = data_frame['Sale Amount'].str.replace(r'\$', '')
data_frame['Sale Amount'] = data_frame['Sale Amount'].str.replace(',', '')
data_frame['Sale Amount'] = data_frame['Sale Amount'].astype(float)
data_frame_value_meets_condition = \
data_frame[data_frame['Sale Amount'].astype(float) > 1400.0]
This is the output of the command window after running with the corrected code:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition.py input_files\sal
es_2013.xlsx output_files\pandas_output8.xlsx
script_name: pandas_value_meets_condition.py
input_file: input_files\sales_2013.xlsx
output_file: output_files\pandas_output8.xlsx
0 1200.0
1 1425.0
2 1390.0
3 1257.0
4 1725.0
5 1995.0
Name: Sale Amount, dtype: float64
C:\ProjectsPy\Foundations>
|
Ted Ensminger |
Nov 19, 2016 |
Mar 24, 2017 |
| Printed |
Page 125
Line 24 in the code snippet (page 125), and line 27 in the code snippet file |
The base Python snippet code '9excel_value_meets_condition_all_worksheets.py' (page 125) contains a major bug that will cause Python to throw a 'TypeError' exception.
Line 24 in the code snippet (page 125), and line 27 in the code snippet file, is testing the value in the 'sale_amount' variable for a minimum threshold value of 2000.0. The input file (spreadsheet) contains strings in the sale_amount column which is column 3. The sale_amount column values contain embedded dollar signs and commas.
You can't compare a string ($2,135.00) against a floating-point value (2000.0). Take note that I created the input file following the instructions on pages 102 through 103.
This is the command line output after running the script:
C:\ProjectsPy\Foundations>python 9excel_value_meets_condition_all_worksheets.py
input_files\sales_2013.xlsx output_files\9output.xlsx
Traceback (most recent call last):
File "9excel_value_meets_condition_all_worksheets.py", line 27, in <module>
if sale_amount > threshold:
TypeError: unorderable types: str() > float()
C:\ProjectsPy\Foundations>
This is one solution to correct this problem:
sale_amount = sale_amount.replace(r"$", "")
sale_amount = sale_amount.replace(r",", "")
sale_amount = float(sale_amount)
if sale_amount > threshold:
This is the output of the command window after running with the corrected code:
C:\ProjectsPy\Foundations>python 9excel_value_meets_condition_all_worksheets.py
input_files\sales_2013.xlsx output_files\9output.xlsx
C:\ProjectsPy\Foundations>
|
Ted Ensminger |
Nov 21, 2016 |
Mar 24, 2017 |
| Printed |
Page 126
Line 9 in the code snippet (page 126), and line 9 in the code snippet file |
The Pandas snippet code 'pandas_value_meets_condition_all_worksheets.py' (page 126) contains a major bug that will cause Pandas to throw a 'ValueError' exception.
Line 9 in the code snippet (page 126), and line 9 in the code snippet file, is testing the value in the 'Sale Amount' variable for a minimum threshold value of 2000.0. The input file (spreadsheet) contains strings in the 'Sale Amount' column which is column 3. The 'Sale Amount' column values contain embedded dollar signs and commas.
You can't compare a string ($2,280.00) against a floating-point value (2000.0). Take note that I created the input file following the instructions on pages 102 through 103.
This is the offending code (lines 8 and 9):
for worksheet_name, data in data_frame.items():
row_output.append(data[data['Sale Amount'].astype(float) > 2000.0])
This is the command line output after running the script:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition_all_worksheets.py
input_files\sales_2013.xlsx output_files\pandas_output13.xlsx
Traceback (most recent call last):
File "pandas_value_meets_condition_all_worksheets.py", line 9, in <module>
row_output.append(data[data['Sale Amount'].astype(float) > 2000.0])
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\generic.py", line 2
950, in astype
raise_on_error=raise_on_error, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2938, in astype
return self.apply('astype', dtype=dtype, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2890, in apply
applied = getattr(b, f)(**kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
434, in astype
values=values, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
477, in _astype
values = com._astype_nansafe(values.ravel(), dtype, copy=True)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\common.py", line 19
20, in _astype_nansafe
return arr.astype(dtype)
ValueError: could not convert string to float: '$2,280.00'
C:\ProjectsPy\Foundations>
Base Python would throw a 'TypeError' exception when it encounters a type comparision exception. The last line of the Traceback (above) tells you
that Pandas threw a 'ValueError' exception because it 'could not convert string to float', therefore, the comparison test was never reached.
This is one solution to correct this problem:
for worksheet_name, data in data_frame.items():
data['Sale Amount'] = data['Sale Amount'].str.replace(r'\$', '')
data['Sale Amount'] = data['Sale Amount'].str.replace(r',', '')
data['Sale Amount'] = data['Sale Amount'].astype(float)
print(data['Sale Amount']) # Dump 'Sale Amount' values
row_output.append(data[data['Sale Amount'].astype(float) > 2000.0])
This is the output of the command window after running with the corrected code:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition_all_worksheets.py
input_files\sales_2013.xlsx output_files\pandas_output13.xlsx
0 1115.0
1 1367.0
2 2135.0
3 1346.0
4 1560.0
5 1852.0
Name: Sale Amount, dtype: float64
0 1200.0
1 1425.0
2 1390.0
3 1257.0
4 1725.0
5 1995.0
Name: Sale Amount, dtype: float64
0 1350.0
1 1167.0
2 1789.0
3 2042.0
4 1511.0
5 2280.0
Name: Sale Amount, dtype: float64
C:\ProjectsPy\Foundations>
|
Ted Ensminger |
Nov 21, 2016 |
Mar 24, 2017 |
| Printed |
Page 131
Line 11 in the code snippet |
The pandas snippet code 'pandas_value_meets_condition_set_of_worksheets.py' (page 131) contains a major bug that will cause Pandas to throw a 'ValueError' exception.
Line 11 in the code snippet (page 131), and line 15 in the code snippet file, is testing the value in the 'sale_amount' column for a minimum 'threshold' value of 1900.0. The input file (spreadsheet) contains strings in the sale_amount column which is column 3. The sale amounts contain embedded dollar signs and commas.
You can't compare a string against a floating-point value (1900.0). Take note that I created the input file following the instructions on pages 102 through 103.
This is the command line output after running the script:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition_set_of_worksheets.
py input_files\sales_2013.xlsx output_files\pandas_output15.xlsx
Traceback (most recent call last):
File "pandas_value_meets_condition_set_of_worksheets.py", line 15, in <module>
row_list.append(data[data['Sale Amount'].astype(float) > threshold])
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\generic.py", line 2
950, in astype
raise_on_error=raise_on_error, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2938, in astype
return self.apply('astype', dtype=dtype, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
2890, in apply
applied = getattr(b, f)(**kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
434, in astype
values=values, **kwargs)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\internals.py", line
477, in _astype
values = com._astype_nansafe(values.ravel(), dtype, copy=True)
File "C:\Users\Ted\Anaconda3\lib\site-packages\pandas\core\common.py", line 19
20, in _astype_nansafe
return arr.astype(dtype)
ValueError: could not convert string to float: '$1,995.00'
C:\ProjectsPy\Foundations>
This is one solution to correct this problem (add code after line 10 in print snippet and line 14 in the code file).
I added two print statements to print the column's type (dtype). They will show the dtype before and after the
data values are edited.:
print("data['Sale Amount'].dtype - before: ", (data['Sale Amount'].dtype)) # Print dtype
data['Sale Amount'] = data['Sale Amount'].str.replace(r'\$', '')
data['Sale Amount'] = data['Sale Amount'].str.replace(',', '')
print("data['Sale Amount'].dtype - after: ", (data['Sale Amount'].dtype)) # Print dtype
This is the output of the command window after running with the corrected code:
C:\ProjectsPy\Foundations>python pandas_value_meets_condition_set_of_worksheets.
py input_files\sales_2013.xlsx output_files\pandas_output15.xlsx
data['Sale Amount'].dtype - before: object
data['Sale Amount'].dtype - after: float64
data['Sale Amount'].dtype - before: object
data['Sale Amount'].dtype - after: float64
C:\ProjectsPy\Foundations>
|
Ted Ensminger |
Dec 01, 2016 |
Mar 24, 2017 |
| Printed |
Page 136
Line 15 in the code snippet |
The Base Python snippet code '13excel_concat_data_from_multiple_workbooks.py' (page 136) contains an improperly formatted print statement that will cause Python to throw a 'SyntaxError' exception.
Line 15 in the code snippet (page 136), and line 18 in the code snippet file, has a print statement that does not contain the opening and closing parentheses.
This is the offending code:
print os.path.basename(input_file)
This is the corrected code:
print (os.path.basename(input_file))
|
Ted Ensminger |
Dec 04, 2016 |
Mar 24, 2017 |