finished

practice1/.gitignore

@@ -0,0 +1,2 @@
+.venv
+.~lock*

practice1/country_codes.csv

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+Afghanistan,AF
+Åland Islands,AX
+Albania,AL
+Algeria,DZ
+American Samoa,AS
+Andorra,AD
+Angola,AO
+Anguilla,AI
+Antarctica,AQ
+Antigua and Barbuda,AG
+Argentina,AR
+Armenia,AM
+Aruba,AW
+Australia,AU
+Austria,AT
+Azerbaijan,AZ
+Bahamas,BS
+Bahrain,BH
+Bangladesh,BD
+Barbados,BB
+Belarus,BY
+Belgium,BE
+Belize,BZ
+Benin,BJ
+Bermuda,BM
+Bhutan,BT
+"Bolivia, Plurinational State of",BO
+"Bonaire, Sint Eustatius and Saba",BQ
+Bosnia and Herzegovina,BA
+Botswana,BW
+Bouvet Island,BV
+Brazil,BR
+British Indian Ocean Territory,IO
+Brunei Darussalam,BN
+Bulgaria,BG
+Burkina Faso,BF
+Burundi,BI
+Cambodia,KH
+Cameroon,CM
+Canada,CA
+Cape Verde,CV
+Cayman Islands,KY
+Central African Republic,CF
+Chad,TD
+Chile,CL
+Shanghai-China,CN
+Christmas Island,CX
+Cocos (Keeling) Islands,CC
+Colombia,CO
+Comoros,KM
+Congo,CG
+"Congo, the Democratic Republic of the",CD
+Cook Islands,CK
+Costa Rica,CR
+Côte d'Ivoire,CI
+Croatia,HR
+Cuba,CU
+Curaçao,CW
+Cyprus,CY
+Czech Republic,CZ
+Denmark,DK
+Djibouti,DJ
+Dominica,DM
+Dominican Republic,DO
+Ecuador,EC
+Egypt,EG
+El Salvador,SV
+Equatorial Guinea,GQ
+Eritrea,ER
+Estonia,EE
+Ethiopia,ET
+Falkland Islands (Malvinas),FK
+Faroe Islands,FO
+Fiji,FJ
+Finland,FI
+France,FR
+French Guiana,GF
+French Polynesia,PF
+French Southern Territories,TF
+Gabon,GA
+Gambia,GM
+Georgia,GE
+Germany,DE
+Ghana,GH
+Gibraltar,GI
+Greece,GR
+Greenland,GL
+Grenada,GD
+Guadeloupe,GP
+Guam,GU
+Guatemala,GT
+Guernsey,GG
+Guinea,GN
+Guinea-Bissau,GW
+Guyana,GY
+Haiti,HT
+Heard Island and McDonald Islands,HM
+Holy See (Vatican City State),VA
+Honduras,HN
+Hong Kong-China,HK
+Hungary,HU
+Iceland,IS
+India,IN
+Indonesia,ID
+"Iran, Islamic Republic of",IR
+Iraq,IQ
+Ireland,IE
+Isle of Man,IM
+Israel,IL
+Italy,IT
+Jamaica,JM
+Japan,JP
+Jersey,JE
+Jordan,JO
+Kazakhstan,KZ
+Kenya,KE
+Kiribati,KI
+"Korea, Democratic People's Republic of",KP
+S.Korea,KR
+Kuwait,KW
+Kyrgyzstan,KG
+Lao People's Democratic Republic,LA
+Latvia,LV
+Lebanon,LB
+Lesotho,LS
+Liberia,LR
+Libya,LY
+Liechtenstein,LI
+Lithuania,LT
+Luxembourg,LU
+Macau-China,MO
+"Macedonia, the Former Yugoslav Republic of",MK
+Madagascar,MG
+Malawi,MW
+Malaysia,MY
+Maldives,MV
+Mali,ML
+Malta,MT
+Marshall Islands,MH
+Martinique,MQ
+Mauritania,MR
+Mauritius,MU
+Mayotte,YT
+Mexico,MX
+"Micronesia, Federated States of",FM
+"Moldova, Republic of",MD
+Monaco,MC
+Mongolia,MN
+Montenegro,ME
+Montserrat,MS
+Morocco,MA
+Mozambique,MZ
+Myanmar,MM
+Namibia,NA
+Nauru,NR
+Nepal,NP
+Netherlands,NL
+New Caledonia,NC
+New Zealand,NZ
+Nicaragua,NI
+Niger,NE
+Nigeria,NG
+Niue,NU
+Norfolk Island,NF
+Northern Mariana Islands,MP
+Norway,NO
+Oman,OM
+Pakistan,PK
+Palau,PW
+"Palestine, State of",PS
+Panama,PA
+Papua New Guinea,PG
+Paraguay,PY
+Peru,PE
+Philippines,PH
+Pitcairn,PN
+Poland,PL
+Portugal,PT
+Puerto Rico,PR
+Qatar,QA
+Réunion,RE
+Romania,RO
+Russian Federation,RU
+Rwanda,RW
+Saint Barthélemy,BL
+"Saint Helena, Ascension and Tristan da Cunha",SH
+Saint Kitts and Nevis,KN
+Saint Lucia,LC
+Saint Martin (French part),MF
+Saint Pierre and Miquelon,PM
+Saint Vincent and the Grenadines,VC
+Samoa,WS
+San Marino,SM
+Sao Tome and Principe,ST
+Saudi Arabia,SA
+Senegal,SN
+Serbia,RS
+Seychelles,SC
+Sierra Leone,SL
+Singapore,SG
+Sint Maarten (Dutch part),SX
+Slovak Republic,SK
+Slovenia,SI
+Solomon Islands,SB
+Somalia,SO
+South Africa,ZA
+South Georgia and the South Sandwich Islands,GS
+South Sudan,SS
+Spain,ES
+Sri Lanka,LK
+Sudan,SD
+Suriname,SR
+Svalbard and Jan Mayen,SJ
+Swaziland,SZ
+Sweden,SE
+Switzerland,CH
+Syrian Arab Republic,SY
+Taiwan,TW
+Tajikistan,TJ
+"Tanzania, United Republic of",TZ
+Thailand,TH
+Timor-Leste,TL
+Togo,TG
+Tokelau,TK
+Tonga,TO
+Trinidad and Tobago,TT
+Tunisia,TN
+Turkey,TR
+Turkmenistan,TM
+Turks and Caicos Islands,TC
+Tuvalu,TV
+Uganda,UG
+Ukraine,UA
+UAE,AE
+UK,UK
+USA,US
+United States Minor Outlying Islands,UM
+Uruguay,UY
+Uzbekistan,UZ
+Vanuatu,VU
+"Venezuela, Bolivarian Republic of",VE
+Vietnam,VN
+"Virgin Islands, British",VG
+"Virgin Islands, U.S.",VI
+Wallis and Futuna,WF
+Western Sahara,EH
+Yemen,YE
+Zambia,ZM
+Zimbabwe,ZW

practice1/practice1.csv

@@ -0,0 +1,65 @@
+UAE,434,442,448
+Peru,368,384,373
+Ireland,501,523,522
+Cyprus,440,449,438
+Denmark,500,496,498
+Finland,519,524,545
+Slovenia,501,481,514
+S.Korea,554,536,538
+Belgium,515,509,505
+New Zealand,500,512,516
+Kazakhstan,432,393,425
+Switzerland,531,509,515
+Indonesia,375,396,382
+Australia,504,512,521
+Costa Rica,407,441,429
+Latvia,491,489,502
+Romania,445,438,439
+Spain,484,488,496
+Portugal,487,488,489
+Qatar,376,388,384
+Slovak Republic,482,463,471
+Jordan,386,399,409
+Vietnam,511,508,528
+France,495,505,499
+Czech Republic,499,493,508
+Canada,518,523,525
+Malaysia,421,398,420
+Israel,466,486,470
+Iceland,493,483,478
+Japan,536,538,547
+Montenegro,410,422,410
+Albania,394,394,397
+Taiwan,560,523,523
+Estonia,521,516,541
+Turkey,448,475,463
+Luxembourg,490,488,491
+Hungary,477,488,494
+Austria,506,490,506
+Hong Kong-China,561,545,555
+Colombia,376,403,399
+Russian Federation,482,475,486
+Liechtenstein,535,516,525
+Argentina,388,396,406
+Germany,514,508,524
+Italy,485,490,494
+Bulgaria,439,436,446
+Thailand,427,441,444
+Shanghai-China,613,570,580
+Lithuania,479,477,496
+Brazil,391,410,405
+Serbia,449,446,445
+USA,481,498,497
+Mexico,413,424,415
+Singapore,573,542,551
+Croatia,471,485,491
+UK,494,499,514
+Norway,489,504,495
+Uruguay,409,411,416
+Tunisia,388,404,398
+Greece,453,477,467
+Macau-China,538,509,521
+Sweden,478,483,485
+Poland,518,518,526
+Chile,423,441,445
+Netherlands,523,511,522

practice1/res.csv

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+Shanghai-China,613.0,570.0,580.0,CN,587.6666666666666
+Singapore,573.0,542.0,551.0,SG,555.3333333333334
+Hong Kong-China,561.0,545.0,555.0,HK,553.6666666666666
+S.Korea,554.0,536.0,538.0,KR,542.6666666666666
+Japan,536.0,538.0,547.0,JP,540.3333333333334
+Taiwan,560.0,523.0,523.0,TW,535.3333333333334
+Finland,519.0,524.0,545.0,FI,529.3333333333334
+Estonia,521.0,516.0,541.0,EE,526.0
+Liechtenstein,535.0,516.0,525.0,LI,525.3333333333334
+Macau-China,538.0,509.0,521.0,MO,522.6666666666666
+Canada,518.0,523.0,525.0,CA,522.0
+Poland,518.0,518.0,526.0,PL,520.6666666666666
+Netherlands,523.0,511.0,522.0,NL,518.6666666666666
+Switzerland,531.0,509.0,515.0,CH,518.3333333333334
+Vietnam,511.0,508.0,528.0,VN,515.6666666666666
+Germany,514.0,508.0,524.0,DE,515.3333333333334
+Ireland,501.0,523.0,522.0,IE,515.3333333333334
+Australia,504.0,512.0,521.0,AU,512.3333333333334
+Belgium,515.0,509.0,505.0,BE,509.6666666666667
+New Zealand,500.0,512.0,516.0,NZ,509.3333333333333
+UK,494.0,499.0,514.0,UK,502.3333333333333
+Austria,506.0,490.0,506.0,AT,500.6666666666667
+Czech Republic,499.0,493.0,508.0,CZ,500.0
+France,495.0,505.0,499.0,FR,499.6666666666667
+Slovenia,501.0,481.0,514.0,SI,498.6666666666667
+Denmark,500.0,496.0,498.0,DK,498.0
+Norway,489.0,504.0,495.0,NO,496.0
+Latvia,491.0,489.0,502.0,LV,494.0
+USA,481.0,498.0,497.0,US,492.0
+Italy,485.0,490.0,494.0,IT,489.6666666666667
+Luxembourg,490.0,488.0,491.0,LU,489.6666666666667
+Spain,484.0,488.0,496.0,ES,489.3333333333333
+Portugal,487.0,488.0,489.0,PT,488.0
+Hungary,477.0,488.0,494.0,HU,486.3333333333333
+Iceland,493.0,483.0,478.0,IS,484.6666666666667
+Lithuania,479.0,477.0,496.0,LT,484.0
+Croatia,471.0,485.0,491.0,HR,482.3333333333333
+Sweden,478.0,483.0,485.0,SE,482.0
+Russian Federation,482.0,475.0,486.0,RU,481.0
+Israel,466.0,486.0,470.0,IL,474.0
+Slovak Republic,482.0,463.0,471.0,SK,472.0
+Greece,453.0,477.0,467.0,GR,465.6666666666667
+Turkey,448.0,475.0,463.0,TR,462.0
+Serbia,449.0,446.0,445.0,RS,446.6666666666667
+Cyprus,440.0,449.0,438.0,CY,442.3333333333333
+UAE,434.0,442.0,448.0,AE,441.3333333333333
+Romania,445.0,438.0,439.0,RO,440.6666666666667
+Bulgaria,439.0,436.0,446.0,BG,440.3333333333333
+Thailand,427.0,441.0,444.0,TH,437.3333333333333
+Chile,423.0,441.0,445.0,CL,436.3333333333333
+Costa Rica,407.0,441.0,429.0,CR,425.6666666666667
+Mexico,413.0,424.0,415.0,MX,417.3333333333333
+Kazakhstan,432.0,393.0,425.0,KZ,416.6666666666667
+Montenegro,410.0,422.0,410.0,ME,414.0
+Malaysia,421.0,398.0,420.0,MY,413.0
+Uruguay,409.0,411.0,416.0,UY,412.0
+Brazil,391.0,410.0,405.0,BR,402.0
+Jordan,386.0,399.0,409.0,JO,398.0
+Tunisia,388.0,404.0,398.0,TN,396.6666666666667
+Argentina,388.0,396.0,406.0,AR,396.6666666666667
+Albania,394.0,394.0,397.0,AL,395.0
+Colombia,376.0,403.0,399.0,CO,392.6666666666667
+Indonesia,375.0,396.0,382.0,ID,384.3333333333333
+Qatar,376.0,388.0,384.0,QA,382.6666666666667
+Peru,368.0,384.0,373.0,PE,375.0

practice1/test.py

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+import pandas as pd
+from matplotlib import pyplot as plt, colors
+from matplotlib.font_manager import FontProperties
+import numpy as np
+
+subjects = ["Maths", "Reading", "Science"]
+
+data = pd.read_csv("./practice1.csv", names=["country", *subjects])
+
+country_codes = pd.read_csv("./country_codes.csv", names=["country", "code"])
+
+data = data.merge(country_codes, how="outer", on="country")
+
+data = data.dropna(subset=subjects)
+
+data["Average"] = data.loc[:, subjects].mean(axis=1)
+
+data = data.sort_values(by="Average", ascending=False)
+
+data.to_csv("res.csv", index=False, header=False)
+
+if data[data["code"].isna()].size != 0:
+    raise ValueError("NaN country code")
+
+fig, ax = plt.subplots(nrows=4)
+
+fig.set_size_inches(16, 11.69)
+
+positions = np.array(list(map(str,range(1, len(data.index)+1))))
+
+x = data["code"] + "\n" + positions
+
+# colors=("#ef476f", "#ffd166", "#06d6a0", "#118ab2", "#073B4C")
+
+colors=("tab:blue", "tab:orange", "tab:green", "tab:red", "tab:grey")
+
+subjects_labels = ("🔢", "📚", "🔬", "")
+
+for i, subj in enumerate((*subjects, "Average")):
+    bar = ax[i].bar(x, data[subj], color=colors[i])
+
+    bar_labels = list(map(lambda j: str(int(data[subj][data.index[j]])) if data["code"][data.index[j]] == "UK" else "", range(len(data.index))))
+
+    ax[i].bar_label(bar, labels=bar_labels, weight="bold")
+
+    ax[i].set_title(subjects_labels[i])
+
+    ax[i].autoscale(tight=True)
+
+    ax[i].set_ylim(350)
+
+    mean = int(data[subj].mean())
+
+    ax[i].set_yticks(list(set((*ax[i].get_yticks(), mean, 650))))
+
+    for label in ax[i].get_xticklabels():
+        if "UK" in label.get_text():
+            label.set(fontweight="bold")
+
+    for label in ax[i].get_yticklabels():
+        if label.get_text() == str(mean):
+            label.set(fontweight="bold")
+
+    ax[i].hlines([mean], 0, 1, transform=ax[i].get_yaxis_transform(), color=colors[-1])
+
+    ax[i].spines['top'].set_visible(False)
+    ax[i].spines['right'].set_visible(False)
+    ax[i].spines['bottom'].set_visible(False)
+    ax[i].spines['left'].set_visible(False)
+    # ax[i].grid()
+
+fig.tight_layout()
+
+fig.savefig("test.png")