Discuss the original sources of this data and any important issues or cautions related to the way this data was created.
If this data is sourced from scanned images, then it may help to include an example image here. This gives students insights into how the data was originally collected in raw form.
# Loading the Data
import pandas as pd
# Read the CSV file into a Pandas data frame:
df = pd.read_csv("mydata.csv")
# Show the first three rows
df.head(n=3)
df.describe()
--------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) <ipython-input-1-e89869e48309> in <module>() 3 4 # Read the CSV file into a Pandas data frame: ----> 5 df = pd.read_csv("mydata.csv") 6 7 # Show the first three rows /opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in parser_f(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, doublequote, delim_whitespace, low_memory, memory_map, float_precision) 676 skip_blank_lines=skip_blank_lines) 677 --> 678 return _read(filepath_or_buffer, kwds) 679 680 parser_f.__name__ = name /opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in _read(filepath_or_buffer, kwds) 438 439 # Create the parser. --> 440 parser = TextFileReader(filepath_or_buffer, **kwds) 441 442 if chunksize or iterator: /opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in __init__(self, f, engine, **kwds) 785 self.options['has_index_names'] = kwds['has_index_names'] 786 --> 787 self._make_engine(self.engine) 788 789 def close(self): /opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in _make_engine(self, engine) 1012 def _make_engine(self, engine='c'): 1013 if engine == 'c': -> 1014 self._engine = CParserWrapper(self.f, **self.options) 1015 else: 1016 if engine == 'python': /opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py in __init__(self, src, **kwds) 1706 kwds['usecols'] = self.usecols 1707 -> 1708 self._reader = parsers.TextReader(src, **kwds) 1709 1710 passed_names = self.names is None pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader.__cinit__() pandas/_libs/parsers.pyx in pandas._libs.parsers.TextReader._setup_parser_source() FileNotFoundError: File b'mydata.csv' does not exist
After you run the cell above, you will see the first three rows printed out by the Pandas head() function. Then there is also some text that is output by the describe() function. For more information about Pandas data frame functions, see the documentation:
In order to further explore the dataset in depth, we may rely on Pandas functions and raw row data to discover the following information:
Activity: Explore this dataset using Pandas data frame functions and identify the information above. Record what you discover in the Markdown cell below.
(This area provided for students to record their notes on the dataset.)