Turn your Jupyter Notebook into interactive Presentation Slides¶

This is demo. If you're looking for a more detailed understanding and want to follow along step by step with thorough explanations, we highly recommend you to read our article below:

👉 https://digitalhumanities.hkust.edu.hk/tutorials/turn-your-jupyter-notebook-into-interactive-presentation-slides-using-anaconda/

👉 Slide type of this cell: Slide

Data file¶

Download the data file from our github repo

👉 Slide type of this cell: Slide

Data pre-processing¶

The code provided in this section represents the pre-processing steps that were explained in our first lesson about data cleaning.

# 👉 Slide type of this cell: Fragement
    
import pandas as pd

# change the filepath according to your file location
# Download the Excel here: https://bit.ly/hkust-dh-github-data-threadbound
# Save the file to the same folder of this Jupyter Notebook
filepath = 'data_dh-tutorial_rse-ChiBksBefore1949-ThreadBound.xlsx'

# read data from Excel file
data = pd.read_excel(filepath, sheet_name='data')

# make a copy of the original dataframe "data", and named the copy as "data2"
data2 = data.copy()

# rename column name - from "year published" to "year"
data2.rename(columns={'year published':'year'}, inplace=True)

# group the individual years into broader time periods
data2['Period'] = ['16th century' if 1501 <= year <= 1600 else '17th century' if 1601 <= year <= 1700 else '18th century' if 1701 <= year <= 1800 else '19th century' if 1801 <= year <= 1900 else '20th century' if 1901 <= year <= 2000 else "Ungrouped" for year in data2['year']]

👉 Slide type of this cell: Sub-Slide

Dataframe preview¶

# 👉 Slide type of this cell: Fragment
data2.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 106 entries, 0 to 105
Data columns (total 3 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   year             106 non-null    int64 
 1   number of items  106 non-null    int64 
 2   Period           106 non-null    object
dtypes: int64(2), object(1)
memory usage: 2.6+ KB

# 👉 Slide type of this cell: Sub-Slide
data2
See Full Dataframe in Mito
year number of items Period
0 1600 1 16th century
1 1655 1 17th century
2 1705 1 18th century
3 1709 1 18th century
4 1748 1 18th century
5 1749 1 18th century
6 1781 1 18th century
7 1786 1 18th century
8 1795 1 18th century
9 1800 1 18th century
10 1810 1 19th century
11 1813 1 19th century
12 1817 1 19th century
13 1821 1 19th century
14 1828 1 19th century
15 1832 1 19th century
16 1838 1 19th century
17 1844 1 19th century
18 1845 1 19th century
19 1846 2 19th century
20 1847 1 19th century
21 1848 1 19th century
22 1849 2 19th century
23 1850 2 19th century
24 1851 4 19th century
25 1852 1 19th century
26 1853 1 19th century
27 1860 1 19th century
28 1861 1 19th century
29 1862 1 19th century
... ... ... ...
76 1920 51 20th century
77 1921 11 20th century
78 1922 14 20th century
79 1923 8 20th century
80 1924 11 20th century
81 1925 14 20th century
82 1926 11 20th century
83 1927 6 20th century
84 1928 7 20th century
85 1929 7 20th century
86 1930 20 20th century
87 1931 9 20th century
88 1932 10 20th century
89 1933 14 20th century
90 1934 16 20th century
91 1935 17 20th century
92 1936 24 20th century
93 1937 9 20th century
94 1938 4 20th century
95 1939 6 20th century
96 1940 13 20th century
97 1941 7 20th century
98 1942 6 20th century
99 1943 4 20th century
100 1944 7 20th century
101 1945 10 20th century
102 1946 4 20th century
103 1947 5 20th century
104 1948 6 20th century
105 1949 3 20th century

👉 Slide type of this cell: Slide

Data Visualization¶

👉 Slide type of this cell: Slide

Plotly chart - example¶

👉 Slide type of this cell: Slide

Plotly chart - another example¶

HKUST Digital Humanities Initiative¶

Let's read our article below. We will walk you through the steps of converting Jupyter Notebook to an interactive presentation slide. https://digitalhumanities.hkust.edu.hk/tutorials/turn-your-jupyter-notebook-into-interactive-presentation-slides-using-anaconda/

💬 Feel free to get in touch with us!

The HKUST Digital Humanities Initiative is a collaborative community aimed at bringing together faculty, library, and students to explore digital humanities skills and develop innovative digital projects. It bridges the gap between science and the humanities through digital methods and practices.