unnamed_1 stringlengths 3 278 ⌀ | unnamed_2 stringlengths 3 10 ⌀ | unnamed_3 float64 9.83k 15.6M ⌀ | unnamed_4 float64 1 2 ⌀ | unnamed_5 float64 0.65 0.97 ⌀ | unnamed_6 float64 0.03 0.28 ⌀ | unnamed_7 float64 0 0.08 ⌀ | unnamed_8 float64 0 0.01 ⌀ | unnamed_9 float64 0 0 ⌀ | unnamed_10 float64 8.06k 13.6M ⌀ | unnamed_11 float64 1.18k 1.89M ⌀ | unnamed_12 float64 0 115k ⌀ | unnamed_13 float64 0 4.01k ⌀ | unnamed_14 float64 0 0 ⌀ | unnamed_15 float64 0 119k ⌀ | unnamed_16 float64 1 2 ⌀ | unnamed_17 float64 0.57 0.93 ⌀ | unnamed_18 float64 0.06 0.33 ⌀ | unnamed_19 float64 0 0.12 ⌀ | unnamed_20 float64 0 0.03 ⌀ | unnamed_21 float64 0 0 ⌀ | unnamed_22 float64 7.32k 13M ⌀ | unnamed_23 float64 1.37k 2.24M ⌀ | unnamed_24 float64 0 305k ⌀ | unnamed_25 float64 0 9.88k ⌀ | unnamed_26 float64 0 0 ⌀ | unnamed_27 float64 0 315k ⌀ | esa_source stringclasses 1
value | esa_processed stringdate 2026-04-18 00:00:00 2026-04-18 00:00:00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
KOULIKORO | Koulikoro | 258,339 | 1 | 0.91 | 0.09 | 0 | 0 | 0 | 235,088.49 | 23,250.51 | 0 | 0 | 0 | 0 | 1 | 0.88 | 0.12 | 0 | 0 | 0 | 227,338.32 | 31,000.68 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
null | Dire | 134,559 | 1 | 0.91 | 0.07 | 0.02 | 0 | 0 | 122,448.69 | 9,419.13 | 2,691.18 | 0 | 0 | 2,691.18 | 1 | 0.84 | 0.12 | 0.04 | 0 | 0 | 113,029.56 | 16,147.08 | 5,382.36 | 0 | 0 | 5,382.36 | HDX | 2026-04-18 |
null | Djenné | 255,577 | 1 | 0.9 | 0.1 | 0 | 0 | 0 | 230,019.3 | 25,557.7 | 0 | 0 | 0 | 0 | 1 | 0.83 | 0.15 | 0.02 | 0 | 0 | 212,128.91 | 38,336.55 | 5,111.54 | 0 | 0 | 5,111.54 | HDX | 2026-04-18 |
null | Kolondièba | 247,104 | 1 | 0.84 | 0.15 | 0.01 | 0 | 0 | 207,567.36 | 37,065.6 | 2,471.04 | 0 | 0 | 2,471.04 | 1 | 0.81 | 0.17 | 0.02 | 0 | 0 | 200,154.24 | 42,007.68 | 4,942.08 | 0 | 0 | 4,942.08 | HDX | 2026-04-18 |
null | Barouéli | 248,816 | 1 | 0.91 | 0.09 | 0 | 0 | 0 | 226,422.56 | 22,393.44 | 0 | 0 | 0 | 0 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 221,446.24 | 27,369.76 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
null | Niafunké | 215,275 | 2 | 0.67 | 0.26 | 0.06 | 0.01 | 0 | 144,234.25 | 55,971.5 | 12,916.5 | 2,152.75 | 0 | 15,069.25 | 2 | 0.58 | 0.3 | 0.1 | 0.02 | 0 | 124,859.5 | 64,582.5 | 21,527.5 | 4,305.5 | 0 | 25,833 | HDX | 2026-04-18 |
null | Kéniéba | 241,665 | 1 | 0.84 | 0.16 | 0 | 0 | 0 | 202,998.6 | 38,666.4 | 0 | 0 | 0 | 0 | 1 | 0.81 | 0.17 | 0.02 | 0 | 0 | 195,748.65 | 41,083.05 | 4,833.3 | 0 | 0 | 4,833.3 | HDX | 2026-04-18 |
null | Yanfolila | 260,909 | 1 | 0.87 | 0.13 | 0 | 0 | 0 | 226,990.83 | 33,918.17 | 0 | 0 | 0 | 0 | 1 | 0.81 | 0.17 | 0.02 | 0 | 0 | 211,336.29 | 44,354.53 | 5,218.18 | 0 | 0 | 5,218.18 | HDX | 2026-04-18 |
null | Tominian | 271,216 | 1 | 0.82 | 0.15 | 0.03 | 0 | 0 | 222,397.12 | 40,682.4 | 8,136.48 | 0 | 0 | 8,136.48 | 1 | 0.8 | 0.16 | 0.03 | 0 | 0 | 216,972.8 | 43,394.56 | 8,136.48 | 0 | 0 | 8,136.48 | HDX | 2026-04-18 |
null | Tin-Essako | 9,829 | 1 | 0.82 | 0.12 | 0.06 | 0 | 0 | 8,059.78 | 1,179.48 | 589.74 | 0 | 0 | 589.74 | 2 | 0.8 | 0.14 | 0.06 | 0 | 0 | 7,863.2 | 1,376.06 | 589.74 | 0 | 0 | 589.74 | HDX | 2026-04-18 |
3. Répéter les mêmes étapes pour la situation projetée | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
TOMBOUCTOU | Tombouctou | 156,237 | 2 | 0.74 | 0.2 | 0.06 | 0 | 0 | 115,615.38 | 31,247.4 | 9,374.22 | 0 | 0 | 9,374.22 | 2 | 0.66 | 0.25 | 0.09 | 0 | 0 | 103,116.42 | 39,059.25 | 14,061.33 | 0 | 0 | 14,061.33 | HDX | 2026-04-18 |
null | Niono | 447,517 | 1 | 0.85 | 0.15 | 0 | 0 | 0 | 380,389.45 | 67,127.55 | 0 | 0 | 0 | 0 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 398,290.13 | 49,226.87 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
SIAKASSO | Sikasso | 901,497 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 802,332.33 | 99,164.67 | 0 | 0 | 0 | 0 | 1 | 0.86 | 0.13 | 0.01 | 0 | 0 | 775,287.42 | 117,194.61 | 9,014.97 | 0 | 0 | 9,014.97 | HDX | 2026-04-18 |
MOPTI | Mopti | 452,388 | 1 | 0.94 | 0.05 | 0.01 | 0 | 0 | 425,244.72 | 22,619.4 | 4,523.88 | 0 | 0 | 4,523.88 | 1 | 0.92 | 0.06 | 0.02 | 0 | 0 | 416,196.96 | 27,143.28 | 9,047.76 | 0 | 0 | 9,047.76 | HDX | 2026-04-18 |
TOTAL GENERAL | null | 15,599,002 | null | null | null | null | null | null | 13,587,342.08 | 1,892,885.7 | 114,764.6 | 4,009.62 | 0 | 118,774.22 | null | null | null | null | null | null | 13,045,914.2 | 2,235,422.41 | 305,077.12 | 9,876.11 | 0 | 314,953.23 | HDX | 2026-04-18 |
null | Yelimané | 216,483 | 1 | 0.92 | 0.08 | 0 | 0 | 0 | 199,164.36 | 17,318.64 | 0 | 0 | 0 | 0 | 1 | 0.89 | 0.1 | 0.01 | 0 | 0 | 192,669.87 | 21,648.3 | 2,164.83 | 0 | 0 | 2,164.83 | HDX | 2026-04-18 |
null | G.Rharous | 136,242 | 2 | 0.65 | 0.28 | 0.07 | 0 | 0 | 88,557.3 | 38,147.76 | 9,536.94 | 0 | 0 | 9,536.94 | 2 | 0.57 | 0.33 | 0.1 | 0 | 0 | 77,657.94 | 44,959.86 | 13,624.2 | 0 | 0 | 13,624.2 | HDX | 2026-04-18 |
null | Kangaba | 123,150 | 1 | 0.93 | 0.07 | 0 | 0 | 0 | 114,529.5 | 8,620.5 | 0 | 0 | 0 | 0 | 1 | 0.9 | 0.1 | 0 | 0 | 0 | 110,835 | 12,315 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
null | Bla | 347,933 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 309,660.37 | 38,272.63 | 0 | 0 | 0 | 0 | 1 | 0.86 | 0.14 | 0 | 0 | 0 | 299,222.38 | 48,710.62 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
KAYES | Kayes | 629,362 | 1 | 0.87 | 0.13 | 0 | 0 | 0 | 547,544.94 | 81,817.06 | 0 | 0 | 0 | 0 | 1 | 0.84 | 0.15 | 0.01 | 0 | 0 | 528,664.08 | 94,404.3 | 6,293.62 | 0 | 0 | 6,293.62 | HDX | 2026-04-18 |
null | Ménaka | 66,777 | 1 | 0.88 | 0.1 | 0.02 | 0 | 0 | 58,763.76 | 6,677.7 | 1,335.54 | 0 | 0 | 1,335.54 | 1 | 0.81 | 0.14 | 0.05 | 0 | 0 | 54,089.37 | 9,348.78 | 3,338.85 | 0 | 0 | 3,338.85 | HDX | 2026-04-18 |
2. Pour la SITUATION COURANTE | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Kita | 530,463 | 1 | 0.84 | 0.15 | 0.01 | 0 | 0 | 445,588.92 | 79,569.45 | 5,304.63 | 0 | 0 | 5,304.63 | 1 | 0.82 | 0.16 | 0.02 | 0 | 0 | 434,979.66 | 84,874.08 | 10,609.26 | 0 | 0 | 10,609.26 | HDX | 2026-04-18 |
SEGOU | Ségou | 853,789 | 1 | 0.87 | 0.13 | 0 | 0 | 0 | 742,796.43 | 110,992.57 | 0 | 0 | 0 | 0 | 1 | 0.85 | 0.15 | 0 | 0 | 0 | 725,720.65 | 128,068.35 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
4. Dans la dernière ligne « Total », inscrire la population totale du pays, la population totale en Phase3, 4 et 5 pour la situation courante pour le pays et la population totale en Phase3, 4 et 5 pour la situation projetée pour le pays. Ne rien inscrire dans les autres | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Goundam | 185,687 | 2 | 0.74 | 0.2 | 0.05 | 0.01 | 0 | 137,408.38 | 37,137.4 | 9,284.35 | 1,856.87 | 0 | 11,141.22 | 2 | 0.62 | 0.25 | 0.1 | 0.03 | 0 | 115,125.94 | 46,421.75 | 18,568.7 | 5,570.61 | 0 | 24,139.31 | HDX | 2026-04-18 |
c. Calculer pour finir, en utilisant les pourcentages estimés de ménages en Phase 3, 4 et 5 l’estimation de population totale en insécurité alimentaire pour chaque entité administrative de 3ème niveau | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Yorosso | 259,546 | 1 | 0.88 | 0.12 | 0 | 0 | 0 | 228,400.48 | 31,145.52 | 0 | 0 | 0 | 0 | 1 | 0.85 | 0.13 | 0.02 | 0 | 0 | 220,614.1 | 33,740.98 | 5,190.92 | 0 | 0 | 5,190.92 | HDX | 2026-04-18 |
KIDAL | Kidal | 41,006 | 2 | 0.68 | 0.25 | 0.07 | 0 | 0 | 27,884.08 | 10,251.5 | 2,870.42 | 0 | 0 | 2,870.42 | 2 | 0.66 | 0.27 | 0.07 | 0 | 0 | 27,063.96 | 11,071.62 | 2,870.42 | 0 | 0 | 2,870.42 | HDX | 2026-04-18 |
null | Youwarou | 133,082 | 1 | 0.82 | 0.16 | 0.02 | 0 | 0 | 109,127.24 | 21,293.12 | 2,661.64 | 0 | 0 | 2,661.64 | 2 | 0.73 | 0.25 | 0.02 | 0 | 0 | 97,149.86 | 33,270.5 | 2,661.64 | 0 | 0 | 2,661.64 | HDX | 2026-04-18 |
TOTAL REGION | null | 83,001 | null | null | null | null | null | null | 60,692.42 | 16,666.14 | 5,642.44 | 0 | 0 | 5,642.44 | null | null | null | null | null | null | 59,839.44 | 17,600.98 | 5,560.58 | 0 | 0 | 5,560.58 | HDX | 2026-04-18 |
null | Diéma | 259,720 | 1 | 0.86 | 0.14 | 0 | 0 | 0 | 223,359.2 | 36,360.8 | 0 | 0 | 0 | 0 | 1 | 0.82 | 0.16 | 0.02 | 0 | 0 | 212,970.4 | 41,555.2 | 5,194.4 | 0 | 0 | 5,194.4 | HDX | 2026-04-18 |
null | Kolokani | 285,189 | 1 | 0.83 | 0.15 | 0.02 | 0 | 0 | 236,706.87 | 42,778.35 | 5,703.78 | 0 | 0 | 5,703.78 | 1 | 0.81 | 0.16 | 0.03 | 0 | 0 | 231,003.09 | 45,630.24 | 8,555.67 | 0 | 0 | 8,555.67 | HDX | 2026-04-18 |
null | Macina | 289,550 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 257,699.5 | 31,850.5 | 0 | 0 | 0 | 0 | 1 | 0.86 | 0.14 | 0 | 0 | 0 | 249,013 | 40,537 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
null | Kati | 1,173,570 | 1 | 0.89 | 0.11 | 0 | 0 | 0 | 1,044,477.3 | 129,092.7 | 0 | 0 | 0 | 0 | 1 | 0.83 | 0.15 | 0.02 | 0 | 0 | 974,063.1 | 176,035.5 | 23,471.4 | 0 | 0 | 23,471.4 | HDX | 2026-04-18 |
null | Bankass | 324,694 | 1 | 0.97 | 0.03 | 0 | 0 | 0 | 314,953.18 | 9,740.82 | 0 | 0 | 0 | 0 | 1 | 0.93 | 0.06 | 0.01 | 0 | 0 | 301,965.42 | 19,481.64 | 3,246.94 | 0 | 0 | 3,246.94 | HDX | 2026-04-18 |
null | Dioïla | 599,739 | 1 | 0.9 | 0.1 | 0 | 0 | 0 | 539,765.1 | 59,973.9 | 0 | 0 | 0 | 0 | 1 | 0.87 | 0.12 | 0.01 | 0 | 0 | 521,772.93 | 71,968.68 | 5,997.39 | 0 | 0 | 5,997.39 | HDX | 2026-04-18 |
GAO | Gao | 293,730 | 1 | 0.86 | 0.14 | 0 | 0 | 0 | 252,607.8 | 41,122.2 | 0 | 0 | 0 | 0 | 1 | 0.85 | 0.11 | 0.04 | 0 | 0 | 249,670.5 | 32,310.3 | 11,749.2 | 0 | 0 | 11,749.2 | HDX | 2026-04-18 |
TOTAL REGION | null | 665,000 | null | null | null | null | null | null | 576,471.68 | 82,529.78 | 5,998.54 | 0 | 0 | 5,998.54 | null | null | null | null | null | null | 550,399.2 | 82,478.82 | 32,121.98 | 0 | 0 | 32,121.98 | HDX | 2026-04-18 |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Kadiolo | 298,557 | 1 | 0.85 | 0.15 | 0 | 0 | 0 | 253,773.45 | 44,783.55 | 0 | 0 | 0 | 0 | 1 | 0.82 | 0.17 | 0.01 | 0 | 0 | 244,816.74 | 50,754.69 | 2,985.57 | 0 | 0 | 2,985.57 | HDX | 2026-04-18 |
null | Tessalit | 19,550 | 1 | 0.84 | 0.1 | 0.06 | 0 | 0 | 16,422 | 1,955 | 1,173 | 0 | 0 | 1,173 | 1 | 0.9 | 0.07 | 0.03 | 0 | 0 | 17,595 | 1,368.5 | 586.5 | 0 | 0 | 586.5 | HDX | 2026-04-18 |
null | Bourem | 142,686 | 1 | 0.86 | 0.13 | 0.01 | 0 | 0 | 122,709.96 | 18,549.18 | 1,426.86 | 0 | 0 | 1,426.86 | 1 | 0.81 | 0.15 | 0.04 | 0 | 0 | 115,575.66 | 21,402.9 | 5,707.44 | 0 | 0 | 5,707.44 | HDX | 2026-04-18 |
TOTAL REGION | null | 3,242,001 | null | null | null | null | null | null | 2,847,645.46 | 377,645.36 | 16,710.18 | 0 | 0 | 16,710.18 | null | null | null | null | null | null | 2,735,438.59 | 452,227.67 | 54,334.74 | 0 | 0 | 54,334.74 | HDX | 2026-04-18 |
TOTAL REGION | null | 2,971,001 | null | null | null | null | null | null | 2,632,394.98 | 329,935 | 8,671.02 | 0 | 0 | 8,671.02 | null | null | null | null | null | null | 2,516,219.88 | 408,479.28 | 46,301.84 | 0 | 0 | 46,301.84 | HDX | 2026-04-18 |
null | San | 409,178 | 1 | 0.9 | 0.1 | 0 | 0 | 0 | 368,260.2 | 40,917.8 | 0 | 0 | 0 | 0 | 1 | 0.86 | 0.14 | 0 | 0 | 0 | 351,893.08 | 57,284.92 | 0 | 0 | 0 | 0 | HDX | 2026-04-18 |
null | Abeïbara | 12,616 | 2 | 0.66 | 0.26 | 0.08 | 0 | 0 | 8,326.56 | 3,280.16 | 1,009.28 | 0 | 0 | 1,009.28 | 2 | 0.58 | 0.3 | 0.12 | 0 | 0 | 7,317.28 | 3,784.8 | 1,513.92 | 0 | 0 | 1,513.92 | HDX | 2026-04-18 |
Estimation des populations en insécurité alimentaire aigüe par zone d’analyse | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Ténenkou | 199,793 | 1 | 0.84 | 0.15 | 0.01 | 0 | 0 | 167,826.12 | 29,968.95 | 1,997.93 | 0 | 0 | 1,997.93 | 2 | 0.78 | 0.18 | 0.04 | 0 | 0 | 155,838.54 | 35,962.74 | 7,991.72 | 0 | 0 | 7,991.72 | HDX | 2026-04-18 |
null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
1. Reporter dans « Population Totale » les chiffres les plus récents de population pour l’entité administrative de 3ème niveau. Ces chiffres doivent se trouver dans le Tableau 1. Faire cela pour toutes les zones d’analyse. | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | HDX | 2026-04-18 |
null | Banamba | 234,290 | 1 | 0.92 | 0.08 | 0 | 0 | 0 | 215,546.8 | 18,743.2 | 0 | 0 | 0 | 0 | 1 | 0.9 | 0.09 | 0.01 | 0 | 0 | 210,861 | 21,086.1 | 2,342.9 | 0 | 0 | 2,342.9 | HDX | 2026-04-18 |
TOTAL REGION | null | 2,444,999 | null | null | null | null | null | null | 2,115,193.52 | 324,500.85 | 5,304.63 | 0 | 0 | 5,304.63 | null | null | null | null | null | null | 2,038,762.12 | 371,468.41 | 34,768.47 | 0 | 0 | 34,768.47 | HDX | 2026-04-18 |
TOTAL REGION | null | 828,000 | null | null | null | null | null | null | 608,264 | 171,923.19 | 43,803.19 | 4,009.62 | 0 | 47,812.81 | null | null | null | null | null | null | 533,789.36 | 211,170.44 | 73,164.09 | 9,876.11 | 0 | 83,040.2 | HDX | 2026-04-18 |
null | Bafoulabé | 286,548 | 1 | 0.9 | 0.1 | 0 | 0 | 0 | 257,893.2 | 28,654.8 | 0 | 0 | 0 | 0 | 1 | 0.84 | 0.15 | 0.01 | 0 | 0 | 240,700.32 | 42,982.2 | 2,865.48 | 0 | 0 | 2,865.48 | HDX | 2026-04-18 |
null | Koro | 444,640 | 1 | 0.89 | 0.1 | 0.01 | 0 | 0 | 395,729.6 | 44,464 | 4,446.4 | 0 | 0 | 4,446.4 | 1 | 0.86 | 0.12 | 0.02 | 0 | 0 | 382,390.4 | 53,356.8 | 8,892.8 | 0 | 0 | 8,892.8 | HDX | 2026-04-18 |
Mali: 2015/2016 Food Security IPC analysis | Africa (original)
Size category: n<1K - Formats: parquet - Sector: humanitarian_development - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets help analysts inspect structured evidence, build reproducible workflows, and compare patterns across domains.
Dataset context from the existing Hugging Face card: Mali: 2015/2016 Food Security IPC analysis Publisher: OCHA Mali · Source: HDX · License: cc-by-igo · Updated: 2023-03-03 Abstract The data represents the IPC (Integrated Food Security Phase Classification) analysis as of November 2015 for Mali and its related projection for June - August 2016. Each row in this dataset represents tabular records. Data was last updated on HDX on 2023-03-03. Geographic scope: MLI. Curated into ML-ready Parquet format by Electric Sheep… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis.
Dataset Profile
| Field | Value |
|---|---|
| Hugging Face repo | electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis |
| Sector | humanitarian_development |
| Topic tags | humanitarian, hdx, electric-sheep-africa, food-security, integrated-food-security-phase-classification-ipc, nutrition, mli |
| Modalities | tabular, text |
| Formats | parquet |
| Size category | n<1K |
| Countries | Mali |
| ISO3 coverage | MLI |
| Last modified on HF | 2026-04-20 08:36:52+00:00 |
| Inventory snapshot | 2026-07-16T16:00:34Z |
How To Read This Dataset
- Start from the repository files and the dataset viewer when available.
- Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
- Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
- Preserve missing values until you have a defensible imputation rule.
Usage
from datasets import load_dataset
ds = load_dataset("electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis")
print(ds)
split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])
Convert To Pandas When Tabular
from datasets import Dataset
first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
df = first_split.to_pandas()
print(df.head())
Data Quality Notes
- This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
- Exact schema, row counts, and source files should be inspected in the repository data files.
- Metadata gaps from the inventory: upstream_publisher.
- Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.
Source And Provenance
- Source context: original
- Publisher/source attribution: original
- License: CC BY 4.0
- Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis
- Inventory retrieved at:
2026-07-16T16:00:34Z
Suggested Analyses
- Inspect schema and missingness before modeling.
- Profile variables by geography, time, and subgroup columns where present.
- Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
- Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.
Citation
@misc{electric_sheep_africa_africa_mali_2015_2016_food_security_ipc_analysis_2026,
title = {Mali: 2015/2016 Food Security IPC analysis | Africa (original)},
author = {original},
year = {2026},
url = {https://huggingface.co/datasets/electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis},
publisher = {Hugging Face Datasets, engineered by Electric Sheep Africa},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-mali-2015-2016-food-security-ipc-analysis}}
}
License
Released under CC BY 4.0.
Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.
About Electric Sheep Africa
Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.
Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.
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