Cord Count

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1. Number of Cords

The total number of cords in the khipu and the indicator of its size.

2. Summary Results:

Measure	Result
Number of Khipus That Match	650(100%)
Number of Significant Khipus	121 (19%)
Five most Significant Khipu	AS069, UR093, UR231, UR006, UR113
Image Quilt	Click here

3. Summary Charts:

Code

# Initialize plotly
plotly.offline.init_notebook_mode(connected = False);

# Read in the Fieldmark and its associated dataframe and match dictionary
from fieldmark_khipu_summary import Fieldmark_Num_Cords
aFieldmark = Fieldmark_Num_Cords()
fieldmark_dataframe = aFieldmark.dataframes[0].dataframe
raw_match_dict = aFieldmark.raw_match_dict()
matching_khipus = aFieldmark.matching_khipus() 
unsorted_matching_khipus =  {key:value for (key,value) in aFieldmark.match_vector().items() if (value != 0.0)}
sorted_matching_khipus = [name for (name,value) in sorted(unsorted_matching_khipus.items(), key=lambda x:x[1], reverse=True)]

Code

# Plot Matching khipu
matching_khipus = aFieldmark.matching_khipus() 
matching_values = [raw_match_dict[aKhipuName] for aKhipuName in matching_khipus]
matching_df =  pd.DataFrame(list(zip(matching_khipus, matching_values)), columns =['KhipuName', 'Value'])
fig = px.bar(matching_df, x='KhipuName', y='Value', labels={"KhipuName": "Khipu Name", "Value": "Number of  Cords", }, 
            title=f"Matching Khipu for Number of  Cords",  width=944, height=500).update_layout(showlegend=True).show()

Code

# Plot Significant khipu
significant_khipus = aFieldmark.significant_khipus()
significant_values = [raw_match_dict[aKhipuName] for aKhipuName in significant_khipus]
significant_df =  pd.DataFrame(list(zip(significant_khipus, significant_values)), columns =['KhipuName', 'Value'])
fig = px.bar(significant_df, x='KhipuName', y='Value', labels={"KhipuName": "Khipu Name", "Value": "Number of  Cords", },
             title=f"Significant Khipu  {len(significant_khipus)} for Number of  Cords", width=944, height=500).update_layout(showlegend=True).show()

4. Exploratory Data Analysis

What is the makeup of cords, pendants, top cords, subsidiaries, etc overall?

Code

# Khipu Imports#
(khipu_dict, all_khipus) = kamayuq.fetch_khipus()

num_corded_khipus = sum([aKhipu.num_cc_cords() > 0 for aKhipu in all_khipus])
corded_khipus = [aKhipu for aKhipu in all_khipus]
num_cords = sum([aKhipu.num_cc_cords() for aKhipu in all_khipus])
num_pendants = sum([aKhipu.num_pendant_cords() for aKhipu in all_khipus])
num_top_cords = sum([aKhipu.num_top_cords() for aKhipu in all_khipus])
num_down_pendants = num_pendants - num_top_cords
num_subsidiaries = sum([aKhipu.num_subsidiary_cords() for aKhipu in all_khipus])

print(f"Number of khipus with cords = {num_corded_khipus}")
print(f"Number of all cords (including top cords and subsidiaries) = {num_cords}")
print(f"Number of pendant cords (including top cords) = {num_pendants}")
print(f"Number of pendant cords which are not top cords = {num_down_pendants}")
print(f"Number of subsidiary cords (total) = {num_subsidiaries}")
print(f"Number of top cords (total) = {num_top_cords}")

Number of khipus with cords = 650
Number of all cords (including top cords and subsidiaries) = 55720
Number of pendant cords (including top cords) = 41671
Number of pendant cords which are not top cords = 41295
Number of subsidiary cords (total) = 14046
Number of top cords (total) = 376