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Reference

This file documents the key functions in the Spacewalks tool. It is provided as a reference manual.

add_crew_size_column(df)

Add crew_size column to the dataset containing the value of the crew size

Parameters:

Name Type Description Default
df DataFrame

The input data frame.

 required

Returns:

Name Type Description
df_copy DataFrame

A copy of df with the new crew_size variable added
Source code in eva_data_analysis.py 
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def add_crew_size_column(df):
    """
    Add crew_size column to the dataset containing the value of the crew size

    Args:
        df (pd.DataFrame): The input data frame.

    Returns:
        df_copy (pd.DataFrame): A copy of df with the new crew_size variable added
    """
    print('Adding crew size variable (crew_size) to dataset')
    df_copy = df.copy()
    df_copy["crew_size"] = df_copy["crew"].apply(
        calculate_crew_size
    )
    return df_copy

add_duration_hours_variable(df)

Add duration in hours (duration_hours) variable to the dataset

Parameters:

Name Type Description Default
df DataFrame

The input dataframe.

 required

Returns:

Name Type Description
df_copy DataFrame

A copy of df_ with the new duration_hours variable added
Source code in eva_data_analysis.py 
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def add_duration_hours_variable(df):
    """
    Add duration in hours (duration_hours) variable to the dataset

    Args:
        df (pd.DataFrame): The input dataframe.

    Returns:
        df_copy (pd.DataFrame): A copy of df_ with the new duration_hours variable added
    """
    df_copy = df.copy()
    df_copy["duration_hours"] = df_copy["duration"].apply(
        text_to_duration
    )
    return df_copy

calculate_crew_size(crew)

Calculate the size of the crew for a single crew entry

Parameters:

Name Type Description Default
crew str

The text entry in the crew column containing a list of crew member names

 required

Returns:

Type Description
int

The crew size
Source code in eva_data_analysis.py 
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def calculate_crew_size(crew):
    """
    Calculate the size of the crew for a single crew entry

    Args:
        crew (str): The text entry in the crew column containing a list of crew member names

    Returns:
        (int): The crew size
    """
    if crew.split() == []:
        return None
    else:
        return len(re.split(r';', crew))-1

plot_cumulative_time_in_space(df, graph_file)

Plot the cumulative time spent in space over years

Convert the duration column from strings to number of hours Calculate cumulative sum of durations Generate a plot of cumulative time spent in space over years and save it to the specified location

Parameters:

Name Type Description Default
df DataFrame

The input dataframe.

 required
graph_file str

The path to the output graph file.

 required

Returns:

Type Description
None
Source code in eva_data_analysis.py 
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def plot_cumulative_time_in_space(df, graph_file):
    """
    Plot the cumulative time spent in space over years

    Convert the duration column from strings to number of hours
    Calculate cumulative sum of durations
    Generate a plot of cumulative time spent in space over years and
    save it to the specified location

    Args:
        df (pd.DataFrame): The input dataframe.
        graph_file (str): The path to the output graph file.

    Returns:
        (None):
    """
    print(f'Plotting cumulative spacewalk duration and saving to {graph_file}')
    df = add_duration_hours_variable(df)
    df['cumulative_time'] = df['duration_hours'].cumsum()
    plt.plot(df.date, df.cumulative_time, 'ko-')
    plt.xlabel('Year')
    plt.ylabel('Total time spent in space to date (hours)')
    plt.tight_layout()
    plt.savefig(graph_file)
    plt.show()

read_json_to_dataframe(input_file)

Read the data from a JSON file into a Pandas dataframe. Clean the data by removing any incomplete rows and sort by date

Parameters:

Name Type Description Default
input_file str

The path to the JSON file.

 required

Returns:

Name Type Description
eva_df DataFrame

The cleaned and sorted data as a dataframe structure
Source code in eva_data_analysis.py 
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def read_json_to_dataframe(input_file):
    """
    Read the data from a JSON file into a Pandas dataframe.
    Clean the data by removing any incomplete rows and sort by date

    Args:
        input_file (str): The path to the JSON file.

    Returns:
         eva_df (pd.DataFrame): The cleaned and sorted data as a dataframe structure
    """
    print(f'Reading JSON file {input_file}')
    eva_df = pd.read_json(input_file, convert_dates=['date'])
    eva_df['eva'] = eva_df['eva'].astype(float)
    eva_df.dropna(axis=0, inplace=True)
    eva_df.sort_values('date', inplace=True)
    return eva_df

text_to_duration(duration)

Convert a text format duration "HH:MM" to duration in hours

Parameters:

Name Type Description Default
duration str

The text format duration

 required

Returns:

Name Type Description
duration_hours float

The duration in hours
Source code in eva_data_analysis.py 
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def text_to_duration(duration):
    """
    Convert a text format duration "HH:MM" to duration in hours

    Args:
        duration (str): The text format duration

    Returns:
        duration_hours (float): The duration in hours
    """
    hours, minutes = duration.split(":")
    duration_hours = int(hours) + int(minutes)/60  # there is an intentional bug on this line (should divide by 60 not 6)
    return duration_hours

write_dataframe_to_csv(df, output_file)

Write the dataframe to a CSV file.

Parameters:

Name Type Description Default
df DataFrame

The input dataframe.

 required
output_file str

The path to the output CSV file.

 required

Returns:

Type Description
None
Source code in eva_data_analysis.py 
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def write_dataframe_to_csv(df, output_file):
    """
    Write the dataframe to a CSV file.

    Args:
        df (pd.DataFrame): The input dataframe.
        output_file (str): The path to the output CSV file.

    Returns:
        (None):
    """
    print(f'Saving to CSV file {output_file}')
    df.to_csv(output_file, index=False)