Charles De Dampierre commited on
Commit
e218e4c
1 Parent(s): 026a3b5

commit results

Browse files
Files changed (29) hide show
  1. __pycache__/region_list.cpython-311.pyc +0 -0
  2. app.py +96 -41
  3. data/immaterial_index/figures_trends_R/results/Chinese world.png +3 -0
  4. data/immaterial_index/figures_trends_R/results/Greek World.png +3 -0
  5. data/immaterial_index/figures_trends_R/results/Indian world.png +3 -0
  6. data/immaterial_index/figures_trends_R/results/Latin World.png +3 -0
  7. data/immaterial_index/figures_trends_R/results/Low countries.png +3 -0
  8. data/immaterial_index/figures_trends_R/results/Nordic countries.png +3 -0
  9. data/immaterial_index/figures_trends_R/results/Slav world.png +3 -0
  10. data/immaterial_index/figures_trends_R/results/United Kingdom.png +3 -0
  11. data/immaterial_index/figures_trends_R/results/Western Europe.png +3 -0
  12. data/immaterial_index/figures_trends_R/results/ancient_med.png +2 -2
  13. data/immaterial_index/figures_trends_R/results/byzance.png +2 -2
  14. data/immaterial_index/figures_trends_R/results/china_north_south.png +2 -2
  15. data/immaterial_index/figures_trends_R/results/europe_north_south.png +2 -2
  16. data/immaterial_index/figures_trends_R/results/france.png +2 -2
  17. data/immaterial_index/figures_trends_R/results/india_north_south.png +2 -2
  18. data/immaterial_index/figures_trends_R/results/italy.png +2 -2
  19. data/immaterial_index/figures_trends_R/results/japan.png +2 -2
  20. data/immaterial_index/figures_trends_R/results/japan_north_south.png +2 -2
  21. data/immaterial_index/figures_trends_R/results/mena.png +2 -2
  22. data/immaterial_index/figures_trends_R/results/mena_persian_arab.png +2 -2
  23. data/immaterial_index/figures_trends_R/results/spain.png +2 -2
  24. data/immaterial_index/figures_trends_R/results/yangtze.png +2 -2
  25. data/immaterial_index/figures_trends_R/results_per_capita/Italy.png +3 -0
  26. data/immaterial_index/figures_trends_R/results_per_capita/Japan.png +3 -0
  27. project.toml +1 -0
  28. region_list.py +34 -35
  29. regions.toml +32 -0
__pycache__/region_list.cpython-311.pyc ADDED
Binary file (2.13 kB). View file
 
app.py CHANGED
@@ -2,9 +2,14 @@ import streamlit as st
2
  from PIL import Image
3
  import os
4
  import pandas as pd
 
5
 
 
6
 
7
- @st.cache
 
 
 
8
  def load_data():
9
  df_ind = pd.read_csv("data/df_individuals_score.csv", index_col=[0])
10
  df_ind = df_ind.drop("region_code", axis=1)
@@ -14,13 +19,30 @@ def load_data():
14
  ].astype(str)
15
 
16
  df_ind = df_ind[df_ind["productive_year"] <= 1800]
17
-
18
  return df_ind
19
 
20
 
21
  df_ind = load_data()
22
 
23
- st.title("Our History in Data")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
24
 
25
  # Set the global index path
26
  global_index_path = "data/immaterial_index/figures_trends_R/results"
@@ -41,6 +63,8 @@ maps_path = "data/map_figures"
41
 
42
  from region_list import region_list
43
 
 
 
44
  index_paths = {}
45
 
46
  for region_key in region_list:
@@ -62,9 +86,9 @@ selected_region = st.sidebar.selectbox("Region:", regions, index=regions.index("
62
 
63
  # Display the selected region's images vertically
64
  if selected_region in index_paths:
 
65
 
66
  df = df_ind[df_ind["region_name"] == selected_region]
67
- df["productive_year"] = round(df["productive_year"], 0)
68
  df = df.drop(["region_name", "decade"], axis=1)
69
  df = df[
70
  [
@@ -76,43 +100,74 @@ if selected_region in index_paths:
76
  ]
77
  df = df.sort_values("score", ascending=False)
78
  df = df.rename(columns={"score": "Number of Catalogs"})
79
- df = df.reset_index(drop=True)
80
- st.dataframe(df)
81
 
82
- st.write(f"Number of Cultural producers active before 1800: {len(df)}")
83
-
84
- for key, path in index_paths[selected_region].items():
85
- if os.path.exists(path):
 
 
86
 
87
- if key == "global_index":
88
- st.subheader("Global Index")
89
- st.image(
90
- Image.open(path), caption=key.capitalize(), use_column_width=True
91
- )
92
- elif key == "global_index_per_capita":
93
- st.subheader("Index per capita")
94
- st.image(
95
- Image.open(path), caption=key.capitalize(), use_column_width=True
96
- )
97
- elif key == "unseen_index":
98
- st.subheader("Unsee-Species Index")
99
- st.image(
100
- Image.open(path), caption=key.capitalize(), use_column_width=True
101
- )
102
- elif key == "unseen_index_capita":
103
- st.subheader("Unsee-Species per capita Index")
104
- st.image(
105
- Image.open(path), caption=key.capitalize(), use_column_width=True
106
- )
107
- elif key == "population_index":
108
- st.subheader("Population Index")
109
- st.image(
110
- Image.open(path), caption=key.capitalize(), use_column_width=True
111
- )
112
- elif key == "map":
113
- st.subheader("Maps")
114
- st.sidebar.image(
115
- Image.open(path), caption=key.capitalize(), use_column_width=True
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
116
  )
117
- else:
118
- st.write(f"File for {key.capitalize()} does not exist.")
 
 
 
2
  from PIL import Image
3
  import os
4
  import pandas as pd
5
+ import tomli
6
 
7
+ pd.options.mode.chained_assignment = None
8
 
9
+ st.set_page_config(layout="wide")
10
+
11
+
12
+ @st.cache_data
13
  def load_data():
14
  df_ind = pd.read_csv("data/df_individuals_score.csv", index_col=[0])
15
  df_ind = df_ind.drop("region_code", axis=1)
 
19
  ].astype(str)
20
 
21
  df_ind = df_ind[df_ind["productive_year"] <= 1800]
 
22
  return df_ind
23
 
24
 
25
  df_ind = load_data()
26
 
27
+
28
+ def load_region_descriptions():
29
+ with open("regions.toml", "rb") as toml_file:
30
+ data = tomli.load(toml_file)
31
+ return data
32
+
33
+
34
+ # Function to get description based on selected region
35
+ def get_region_description(region_data, selected_region):
36
+ return region_data[selected_region]["description"]
37
+
38
+
39
+ region_data = load_region_descriptions()
40
+
41
+
42
+ st.sidebar.title("Our History in Data")
43
+ st.sidebar.write(
44
+ "This project is led by Charles de Dampierre, Folgert Karsdorp, Mike Kestemont, Valentin Thouzeau and Nicolas Baumard"
45
+ )
46
 
47
  # Set the global index path
48
  global_index_path = "data/immaterial_index/figures_trends_R/results"
 
63
 
64
  from region_list import region_list
65
 
66
+ region_filtered = list(region_list.keys())
67
+
68
  index_paths = {}
69
 
70
  for region_key in region_list:
 
86
 
87
  # Display the selected region's images vertically
88
  if selected_region in index_paths:
89
+ col1, col2 = st.columns(2)
90
 
91
  df = df_ind[df_ind["region_name"] == selected_region]
 
92
  df = df.drop(["region_name", "decade"], axis=1)
93
  df = df[
94
  [
 
100
  ]
101
  df = df.sort_values("score", ascending=False)
102
  df = df.rename(columns={"score": "Number of Catalogs"})
 
 
103
 
104
+ min_date = region_list[selected_region]["time_range"][0]
105
+ max_date = region_list[selected_region]["time_range"][1]
106
+ df = df[df["productive_year"] >= min_date]
107
+ df = df[df["productive_year"] <= max_date]
108
+ df["productive_year"] = df["productive_year"].astype(int)
109
+ df = df.reset_index(drop=True)
110
 
111
+ # Display the data in the left column
112
+ with col1:
113
+ st.header("Cultural Producers")
114
+ st.dataframe(df)
115
+ st.write(f"Number of Cultural producers active before 1800: {len(df)}")
116
+
117
+ for key, path in index_paths[selected_region].items():
118
+ if os.path.exists(path):
119
+
120
+ if key == "global_index":
121
+ st.subheader("Global Index")
122
+ st.image(
123
+ Image.open(path),
124
+ caption=key.capitalize(),
125
+ use_column_width=True,
126
+ )
127
+ elif key == "global_index_per_capita":
128
+ st.subheader("Index per capita")
129
+ st.image(
130
+ Image.open(path),
131
+ caption=key.capitalize(),
132
+ use_column_width=True,
133
+ )
134
+ elif key == "unseen_index":
135
+ st.subheader("Unsee-Species Index")
136
+ st.image(
137
+ Image.open(path),
138
+ caption=key.capitalize(),
139
+ use_column_width=True,
140
+ )
141
+ elif key == "unseen_index_capita":
142
+ st.subheader("Unsee-Species per capita Index")
143
+ st.image(
144
+ Image.open(path),
145
+ caption=key.capitalize(),
146
+ use_column_width=True,
147
+ )
148
+ elif key == "population_index":
149
+ st.subheader("Population Index")
150
+ st.image(
151
+ Image.open(path),
152
+ caption=key.capitalize(),
153
+ use_column_width=True,
154
+ )
155
+ elif key == "map":
156
+ st.subheader("Maps")
157
+ st.sidebar.image(
158
+ Image.open(path),
159
+ caption=key.capitalize(),
160
+ use_column_width=True,
161
+ )
162
+ else:
163
+ st.write(f"File for {key.capitalize()} does not exist.")
164
+
165
+ with col2:
166
+ try:
167
+ region_description = get_region_description(
168
+ region_data, selected_region
169
  )
170
+ st.header("Analysis")
171
+ st.write(f"{region_description}")
172
+ except:
173
+ st.write("Analysis not ready yet")
data/immaterial_index/figures_trends_R/results/Chinese world.png ADDED

Git LFS Details

  • SHA256: a704ab96dbcff4f78d65ecca424a5d513216e98ddbc770542cf46d526569d31f
  • Pointer size: 131 Bytes
  • Size of remote file: 880 kB
data/immaterial_index/figures_trends_R/results/Greek World.png ADDED

Git LFS Details

  • SHA256: 2607a68e860fd5456b38077901872519b83105550b3325f90b71c9fbcdbf1d04
  • Pointer size: 131 Bytes
  • Size of remote file: 762 kB
data/immaterial_index/figures_trends_R/results/Indian world.png ADDED

Git LFS Details

  • SHA256: 7817e539d6cfc2cb2a98dca3ed1490ebda285776b6cbcfaef168908ce760630b
  • Pointer size: 131 Bytes
  • Size of remote file: 697 kB
data/immaterial_index/figures_trends_R/results/Latin World.png ADDED

Git LFS Details

  • SHA256: 640e2f73a33453805bfa4c3aa53e0bb213603c9a9ab99ee6630635c95b104341
  • Pointer size: 131 Bytes
  • Size of remote file: 686 kB
data/immaterial_index/figures_trends_R/results/Low countries.png ADDED

Git LFS Details

  • SHA256: c4512d8aa60d282e189489dd03d92b260bc2a9f4eeece425e46126effa331bd1
  • Pointer size: 131 Bytes
  • Size of remote file: 966 kB
data/immaterial_index/figures_trends_R/results/Nordic countries.png ADDED

Git LFS Details

  • SHA256: 5f54356903b0e4b3fe095a45406e4bc8e82f9cf431044ae13edb6340f7e0a265
  • Pointer size: 131 Bytes
  • Size of remote file: 788 kB
data/immaterial_index/figures_trends_R/results/Slav world.png ADDED

Git LFS Details

  • SHA256: 15ab2cf608d1d7a0b74977a5c11e0e0b6cec4086a80d9523e8a99c5b44a5f2ab
  • Pointer size: 131 Bytes
  • Size of remote file: 720 kB
data/immaterial_index/figures_trends_R/results/United Kingdom.png ADDED

Git LFS Details

  • SHA256: 5122ed2577f050936a16131e1e6ef94807226c905b41a6a2223894fcf21a0213
  • Pointer size: 131 Bytes
  • Size of remote file: 883 kB
data/immaterial_index/figures_trends_R/results/Western Europe.png ADDED

Git LFS Details

  • SHA256: 3f4c1d647eded4521f7c1f2228af87c83d1bb04cda0b7269b8bfd4a926d7c192
  • Pointer size: 131 Bytes
  • Size of remote file: 935 kB
data/immaterial_index/figures_trends_R/results/ancient_med.png CHANGED

Git LFS Details

  • SHA256: a1f07b637cc27d5d97de2d3a01b2b94ec416707b2f574f4d7fec6051237938a7
  • Pointer size: 132 Bytes
  • Size of remote file: 1.03 MB

Git LFS Details

  • SHA256: f4b32e03f221a4a5ee09d4da6c3710c8c6a4cef0b0f236391031d6574495c7d4
  • Pointer size: 132 Bytes
  • Size of remote file: 1.03 MB
data/immaterial_index/figures_trends_R/results/byzance.png CHANGED

Git LFS Details

  • SHA256: baacd731e0b719239d7049986e956cf834150b23f9e2981009005e73da5e6054
  • Pointer size: 131 Bytes
  • Size of remote file: 702 kB

Git LFS Details

  • SHA256: 4017256fd2272138f7ae07f72410f66fa9a4e635b41e94c46d9b402a6580554c
  • Pointer size: 131 Bytes
  • Size of remote file: 701 kB
data/immaterial_index/figures_trends_R/results/china_north_south.png CHANGED

Git LFS Details

  • SHA256: 56f920e9fe31d8b573a356f1326ff67b3602f646b264f651d7b93139099ef389
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB

Git LFS Details

  • SHA256: dc66d5d609ce5cd3af6d9fea3fbbbeb39ced99554b59426c81494c13ba99f364
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB
data/immaterial_index/figures_trends_R/results/europe_north_south.png CHANGED

Git LFS Details

  • SHA256: 9162a3133c123ae3349029f0c3639da58879071da16b374cafe5dc5f870918ef
  • Pointer size: 132 Bytes
  • Size of remote file: 1.65 MB

Git LFS Details

  • SHA256: 1db59bf36a56d5c29598c10cc08b92a000ee52b01f642d08fa98e842c5908578
  • Pointer size: 132 Bytes
  • Size of remote file: 1.65 MB
data/immaterial_index/figures_trends_R/results/france.png CHANGED

Git LFS Details

  • SHA256: 57434d11918ca0e5cf0a5f6af4b7b7c1504c01f16172b4258f6f75d39657d718
  • Pointer size: 132 Bytes
  • Size of remote file: 1.09 MB

Git LFS Details

  • SHA256: 3c0d9879c0a6971b22b4b933aec3ae0b8b5b83d87d8c9374a6a057e49d6c42bb
  • Pointer size: 132 Bytes
  • Size of remote file: 1.09 MB
data/immaterial_index/figures_trends_R/results/india_north_south.png CHANGED

Git LFS Details

  • SHA256: 6ba30a5491e39aff639e464263f98cf5afce7a06add6bf83376d8a6ff6f8e7ed
  • Pointer size: 131 Bytes
  • Size of remote file: 788 kB

Git LFS Details

  • SHA256: 3e7c632d6f805a9d67145d3797b0ccdd083efc643e351b30c3964ae6ee260323
  • Pointer size: 131 Bytes
  • Size of remote file: 790 kB
data/immaterial_index/figures_trends_R/results/italy.png CHANGED

Git LFS Details

  • SHA256: 4096de52520fa5bc0df45f5be828671004102582481d9c667fa7150c2b2fdbb4
  • Pointer size: 132 Bytes
  • Size of remote file: 1.13 MB

Git LFS Details

  • SHA256: 843da61a5585d834f2b09feccdff075868ab874c1594d760bae392d055fe5e81
  • Pointer size: 132 Bytes
  • Size of remote file: 1.12 MB
data/immaterial_index/figures_trends_R/results/japan.png CHANGED

Git LFS Details

  • SHA256: 190beaf2f3044c851bf48299dec5237a9f9125b4df4d6b5df3917d5f57d73348
  • Pointer size: 131 Bytes
  • Size of remote file: 752 kB

Git LFS Details

  • SHA256: fbb06cbcf45c51b6fb3db4a48d432253683f7acf80c2391c1a33fad781896953
  • Pointer size: 131 Bytes
  • Size of remote file: 750 kB
data/immaterial_index/figures_trends_R/results/japan_north_south.png CHANGED

Git LFS Details

  • SHA256: 7ce9d0c5a3a61df37989af508f5b5a50978d1ce5a9f960a87df08d0f4da7cc91
  • Pointer size: 131 Bytes
  • Size of remote file: 849 kB

Git LFS Details

  • SHA256: a4434e3955dc7bd88d4d0f0ceae3883103ad5f3660b7c1dfe953d73ac230b98f
  • Pointer size: 131 Bytes
  • Size of remote file: 835 kB
data/immaterial_index/figures_trends_R/results/mena.png CHANGED

Git LFS Details

  • SHA256: ec1ae3c94033e13ef29506f4f307516f874a838147fb45239ed66e819fb2c4d3
  • Pointer size: 131 Bytes
  • Size of remote file: 898 kB

Git LFS Details

  • SHA256: 51e7871053f37784dca2f0e29e5f2ef497cc5e04aeb24d7e2dea913d0a71e075
  • Pointer size: 131 Bytes
  • Size of remote file: 900 kB
data/immaterial_index/figures_trends_R/results/mena_persian_arab.png CHANGED

Git LFS Details

  • SHA256: 59ee0b1e4f06eeb0d5983e787e3d9661e04684b23d8d75b6533ddbdc5437fbc3
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB

Git LFS Details

  • SHA256: 72b0b17c168f247bedc051f5016a2320bd5575b20eb8f1cf0c887aed52e5a1d0
  • Pointer size: 132 Bytes
  • Size of remote file: 1.1 MB
data/immaterial_index/figures_trends_R/results/spain.png CHANGED

Git LFS Details

  • SHA256: 5054e746acf04d9a5041a64c79a2e4c26c1690811cd77c09f798706e39fd45a5
  • Pointer size: 131 Bytes
  • Size of remote file: 884 kB

Git LFS Details

  • SHA256: 2abc546ff4a7cd8cca860708f004016e4e2c9303db54ce1389893374e312d999
  • Pointer size: 131 Bytes
  • Size of remote file: 883 kB
data/immaterial_index/figures_trends_R/results/yangtze.png CHANGED

Git LFS Details

  • SHA256: 6e914bfb14ec28ef1616453ced38cc1bb9b59d666b5fe6cf4f3dea4d11cd88a1
  • Pointer size: 131 Bytes
  • Size of remote file: 603 kB

Git LFS Details

  • SHA256: 11d4d0608d0a3130060421661c65141ec5d4727f0587315dc804be7b0b3fba90
  • Pointer size: 131 Bytes
  • Size of remote file: 604 kB
data/immaterial_index/figures_trends_R/results_per_capita/Italy.png ADDED

Git LFS Details

  • SHA256: 8d0e0b82e7886a986a4e935e5431b9b755fa4860afe6bf74156a8ade4949f016
  • Pointer size: 132 Bytes
  • Size of remote file: 1.06 MB
data/immaterial_index/figures_trends_R/results_per_capita/Japan.png ADDED

Git LFS Details

  • SHA256: 17f1c2f91179fe9fe7d6635aeaae79e011060b62f518d3c88b042134ca5ee5a2
  • Pointer size: 131 Bytes
  • Size of remote file: 805 kB
project.toml ADDED
@@ -0,0 +1 @@
 
 
1
+
region_list.py CHANGED
@@ -1,38 +1,37 @@
1
- region_list = [
2
- "Arabic world",
3
- "Japan",
4
- "Italy",
5
- "mediterranean World",
6
- "British Islands",
7
- "Arabian peninsula",
8
- "Northern India",
9
- "South East Asia",
10
- "Muslim world",
11
- "Greek World",
12
- "Central Europe",
13
- "Ottoman Turkey",
14
- "Chinese world",
15
- "German world",
16
- "Korea",
17
- "Spain",
18
- "Greece",
19
- "Balkans",
20
- "Low countries",
21
- "Norway",
22
- "Portugal",
23
- "Ottoman world",
24
- "Yangtze",
25
- "Sweden",
26
- "France",
27
- "Slav world",
28
- "Nordic countries",
29
- "Indian world",
30
- "Latin World",
31
- "United Kingdom",
32
- "Persian world",
33
- "Eastern Europe",
34
- "Western Europe",
35
- ]
36
 
37
 
38
  full_region_list = [
 
1
+ region_list = {
2
+ "Arabic world": {"time_range": [600, 1800]},
3
+ "Italy": {"time_range": [600, 1800]},
4
+ "Japan": {"time_range": [600, 1800]},
5
+ "Mediterranean World": {"time_range": [-800, 500]},
6
+ "British Islands": {"time_range": [600, 1800]},
7
+ "Arabian peninsula": {"time_range": [600, 1800]},
8
+ "South East Asia": {"time_range": [-500, 1800]},
9
+ "Muslim world": {"time_range": [600, 1800]},
10
+ "Greek World": {"time_range": [-800, 500]},
11
+ "Central Europe": {"time_range": [600, 1800]},
12
+ "Ottoman Turkey": {"time_range": [800, 1800]},
13
+ "Chinese world": {"time_range": [-800, 1800]},
14
+ "German world": {"time_range": [600, 1800]},
15
+ "Korea": {"time_range": [600, 1800]},
16
+ "Spain": {"time_range": [600, 1800]},
17
+ "Greece": {"time_range": [600, 1800]},
18
+ "Balkans": {"time_range": [600, 1800]},
19
+ "Low countries": {"time_range": [600, 1800]},
20
+ "Norway": {"time_range": [600, 1800]},
21
+ "Portugal": {"time_range": [600, 1800]},
22
+ "Ottoman world": {"time_range": [1500, 1800]},
23
+ "Yangtze": {"time_range": [-800, 1800]},
24
+ "Sweden": {"time_range": [600, 1800]},
25
+ "France": {"time_range": [600, 1800]},
26
+ "Slav world": {"time_range": [600, 1800]},
27
+ "Nordic countries": {"time_range": [600, 1800]},
28
+ "Indian world": {"time_range": [-800, 1800]},
29
+ "Latin World": {"time_range": [-800, 500]},
30
+ "United Kingdom": {"time_range": [600, 1800]},
31
+ "Persian world": {"time_range": [-800, 1800]},
32
+ "Eastern Europe": {"time_range": [600, 1800]},
33
+ "Western Europe": {"time_range": [600, 1800]},
34
+ }
 
35
 
36
 
37
  full_region_list = [
regions.toml ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ [Japan]
3
+ name = "Japan"
4
+ description = """
5
+
6
+ Our results converge with qualitative and quantitative assessments of economic development Bassino et al.
7
+ (2019); Farris (2009); Nakabayashi et al. (2020) (see Fig. 10).
8
+
9
+ We observe a rise of cultural production from the 7th c. (Nara era) to the 10th c. (Heian era) during which it is estimated that GDP per capita
10
+ increased by 80% Bassino et al. (2019); Nakabayashi et al. (2020). We also observe a continuous rise of
11
+ cultural production from the 16th c. onward during which it is estimated that population tripled (from 10
12
+ to 32 million people), GDP per capita increased by 80%, urbanization was multiplied by 5 from 2.5% to
13
+ 12,5%, with the size of Tokyo and Osaka rivaling that of London or Paris Bassino et al. (2019); Nakabayashi
14
+ et al. (2020). Whereas the previous estimates of the GDP per capita showed extended stagnancy between
15
+ the ninth and 14th c., our results converge with the most recent study, showing a sharp decline in the 12th
16
+ century and recovery from the 13th to 16th centuries Nakabayashi et al. (2020).
17
+
18
+ In line with this study Nakabayashi et al. (2020), our results also suggest that the recovery of the economic development began in
19
+ the 13th during the Kamakura shogunate, earlier than what was previously estimated.
20
+ Our result also allows to have finer temporal estimation. For instance, we observe that the isolation of
21
+ the country (the sakoku policy) starting in 1633 did not impact economic cultural production. At the other
22
+ end of the period, we can see that cultural production was already very robust before the Meiji reforms
23
+ (1868).
24
+
25
+ Also, we document the relative importance of the Kanta and Kansai plains in Japanese history, and
26
+ the progressive shift from the East to the West (see Fig. 11). Despite the political domination of the Kansai
27
+ plain from the 13th onward, the shift in cultural production only occurred during the late 18th c. (Edo
28
+ period)
29
+
30
+
31
+ """
32
+ time_range = [800, 1800]