File:Population of South-Kanto Prefectures, Japan.svg
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Summary
| Description |
English: Population of South-Kanto Prefectures, Japan * South-Kanto : Tokyo,Saitama,Chiba,Kanagawa |
| Date | |
| Source | Own work, Data from Statistics Bureau of Japan 人口推計 |
| Author | Yuasan |
| Permission (Reusing this file) |
CC-0 |
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
 
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This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication. |
| The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.
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Graph Data
import matplotlib as mpl
import matplotlib.ticker as ticker
import matplotlib.pyplot as plt
from cycler import cycler
import pandas as pd
df = pd.read_csv("data.tsv", index_col=0 , sep = "\t").T
fig, ax = plt.subplots(figsize=(10, 5))
mpl.rcParams['axes.xmargin'] = 0.02
plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['Noto Sans Display']
plt.subplots_adjust(left=0.08, bottom=0.08, right=0.96, top=0.91)
ax.plot(df)
ax.legend(df.columns, fontsize=12, ncol=2, loc='upper left', frameon=True, facecolor="#dddddd")
ax.grid(which="both")
ax.set_axisbelow(True)
ax.fill_between( df.index ,0, df["Total"].values, color="lightblue", alpha=0.5)
plt.title("Population of South-Kanto Prefectures, Japan (Statistics Bureau of Japan)", fontsize=16)
plt.tick_params(labelsize=9, pad=4)
plt.ylim([0,40000])
ax.xaxis.set_major_locator(ticker.MultipleLocator(2))
plt.xticks(rotation=35, fontsize=7)
plt.ylabel("1000 person", fontsize=10)
plt.yticks(fontsize=9)
plt.minorticks_on()
plt.grid(which='major',color='#eeeeee',linestyle='-', axis="x")
plt.grid(which='minor', linestyle='None', axis="x")
plt.grid(which='major',color='#bbbbbb',linestyle='-', axis="y")
plt.grid(which='minor',color='#eeeeee',linestyle='-', axis="y")
plt.savefig("image.svg")
1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Total 7678 7855.5 8060.4 7963.1 8334.8 8695 8977.6 9244.8 9513.5 9774.6 9958 10133.3 10427 10714.8 10994.6 11285 11593.8 11788.7 11988.7 12265.6 12586 12613 12819.4 13026.2 13052 9368 10241 11432 12018 12543.5 13051 13616 14141 14627 15044 15424 15851 16315 16797 17310 17864 18426 19041 19683 20344 21017 21557 22193 22834 23472 24113 24818 25480 26065 26576 27042 27415 27758 28103 28413 28697 29002 29315 29632 29950 30273 30614 30949 31265 31549 31796 32047 32249 32386 32473 32577 32708 32880 33066 33214 33418 33687 33905 34148 34328 34479 34713 34985 35227 35395 35618 35684 35720 35820 35958 36131 36328 36506 36682 36856 36914
Saitama 1320 1330.3 1341.1 1367.7 1380 1394 1412.1 1424.9 1437.6 1446.8 1459 1472.8 1484.7 1498.6 1512.2 1529 1534.1 1540.9 1545.9 1552.6 1583 1580.7 1603.8 1635.1 1648 2047 2029 2100 2112.5 2128.8 2146 2167 2190 2213 2237 2263 2286 2310 2339 2378 2431 2497 2588 2718 2864 3015 3161 3328 3492 3670 3866 4062 4266 4475 4658 4821 4964 5091 5208 5318 5420 5520 5615 5700 5784 5864 5954 6071 6195 6308 6405 6486 6567 6640 6703 6759 6804 6841 6877 6906 6938 6977 7000 7028 7046 7054 7079 7106 7136 7161 7195 7209 7216 7228 7247 7267 7288 7307 7325 7342 7345
Chiba 1336 1335.5 1354.3 1382.1 1395.7 1399 1417.2 1426.6 1436.3 1447 1470 1487.6 1502 1517.8 1531.7 1546 1549.7 1554.4 1558.1 1557.3 1561 1556.8 1569.8 1620.9 1659 1967 2009 2113 2123 2121.5 2139 2147 2161 2175 2185 2205 2218 2233 2256 2278 2306 2356 2428 2505 2609 2702 2783 2903 3032 3195 3367 3524 3677 3844 4007 4149 4267 4382 4508 4626 4735 4834 4923 5005 5079 5148 5219 5307 5403 5487 5555 5617 5679 5731 5767 5798 5817 5839 5867 5893 5926 5970 5998 6030 6047 6056 6084 6119 6153 6180 6216 6217 6200 6201 6209 6223 6242 6258 6273 6283 6284
Tokyo 3699 3830.7 3984.2 3859.4 4185.5 4485 4694.4 4897.4 5101.4 5300 5409 5521.1 5755.6 5975.1 6176.9 6370 6586.5 6725.7 6875.6 7081.6 7284 7284.3 7357.8 7332.6 7271 3488 4183 5001 5474.8 5896.3 6278 6712 7109 7469 7774 8037 8349 8681 9011 9349 9684 9967 10224 10470 10668 10869 11018 11162 11286 11367 11408 11520 11611 11639 11647 11674 11674 11669 11659 11637 11618 11626 11650 11700 11759 11829 11888 11887 11873 11863 11856 11894 11887 11849 11796 11774 11808 11881 11939 11983 12064 12165 12271 12388 12482 12577 12704 12848 12973 13048 13159 13198 13234 13307 13399 13515 13646 13768 13887 14007 14048
Kanagawa 1323 1359 1380.8 1353.9 1373.6 1417 1453.9 1495.9 1538.2 1580.8 1620 1651.8 1684.7 1723.3 1773.8 1840 1923.5 1967.7 2009.1 2074.1 2158 2191.2 2288 2437.6 2474 1866 2020 2218 2307.7 2396.9 2488 2590 2681 2770 2848 2919 2998 3091 3191 3305 3443 3606 3801 3990 4203 4431 4595 4800 5024 5240 5472 5712 5926 6107 6264 6398 6510 6616 6728 6832 6924 7022 7127 7227 7328 7432 7553 7684 7794 7891 7980 8050 8116 8166 8207 8246 8279 8319 8383 8432 8490 8575 8636 8702 8753 8792 8846 8912 8965 9006 9048 9060 9070 9084 9103 9126 9152 9173 9197 9224 9237File history
Click on a date/time to view the file as it appeared at that time.
| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 04:02, 9 April 2023 | 900 × 450 (149 KB) | Yuasan | stretch | |
| 06:21, 8 April 2023 | 900 × 450 (153 KB) | Yuasan | Uploaded own work with UploadWizard |
File usage
The following pages on the English Wikipedia use this file (pages on other projects are not listed):
Global file usage
The following other wikis use this file:
- Usage on ja.wikipedia.org
- 南関東
- 都心回帰
- 東京一極集中
- 東京都の人口統計
- Usage on uk.wikipedia.org
- Токійська агломерація