As the most populated country in Africa, Nigeria is often seen as the figure-head for development in the entire continent. When it comes to music, culture, food, etc, the rest fo Africa looks to Nigeria for guidance. However, unlike their cultural success, Nigeria has always lacked when it comes to economic advancement-- in particular, food prices. Despite being blessed with an abundance of natural resources, political issues like corruption, fraud, and the misuse of natural resources has caused the cost of living in Nigeria to skyrocket. As their currency, the Naira continually loses its value over the years, the price of food in the country has gradually increased rendering it almost impossible for middle-class and lower-class citizens afford an appropriate standard of living. The goal of this project is to show the growing food prices in each major Nigerian state against the reduction in value of the Naira
import pandas as pd
data = pd.read_csv('nigeria-food-prices-1.csv')
data
| date | cmname | unit | category | price | currency | country | admname | adm1id | mktname | mktid | cmid | ptid | umid | catid | sn | default | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | #date | #item+name | #item+unit | #item+type | #value | #currency | #country+name | #adm1+name | #adm1+code | #name+market | NaN | #item+code | NaN | NaN | #item+type+code | #meta+id | NaN |
| 1 | 2015-01-15 | Bread - Retail | Unit | cereals and tubers | 140.0 | NGN | Nigeria | Adamawa | 2211 | Mubi | 1980.0 | 55 | 15.0 | 33.0 | 1 | 1980_55_15_33 | NaN |
| 2 | 2015-02-15 | Bread - Retail | Unit | cereals and tubers | 140.0 | NGN | Nigeria | Adamawa | 2211 | Mubi | 1980.0 | 55 | 15.0 | 33.0 | 1 | 1980_55_15_33 | NaN |
| 3 | 2015-03-15 | Bread - Retail | Unit | cereals and tubers | 140.0 | NGN | Nigeria | Adamawa | 2211 | Mubi | 1980.0 | 55 | 15.0 | 33.0 | 1 | 1980_55_15_33 | NaN |
| 4 | 2015-04-15 | Bread - Retail | Unit | cereals and tubers | 140.0 | NGN | Nigeria | Adamawa | 2211 | Mubi | 1980.0 | 55 | 15.0 | 33.0 | 1 | 1980_55_15_33 | NaN |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 13273 | 2018-02-15 | Gari (white) - Wholesale | 100 KG | cereals and tubers | 9880.0 | NGN | Nigeria | Zamfara | 65710 | Kaura Namoda | 1977.0 | 483 | 14.0 | 9.0 | 1 | 1977_483_14_9 | NaN |
| 13274 | 2018-03-15 | Gari (white) - Wholesale | 100 KG | cereals and tubers | 11310.0 | NGN | Nigeria | Zamfara | 65710 | Kaura Namoda | 1977.0 | 483 | 14.0 | 9.0 | 1 | 1977_483_14_9 | NaN |
| 13275 | 2018-04-15 | Gari (white) - Wholesale | 100 KG | cereals and tubers | 12110.0 | NGN | Nigeria | Zamfara | 65710 | Kaura Namoda | 1977.0 | 483 | 14.0 | 9.0 | 1 | 1977_483_14_9 | NaN |
| 13276 | 2018-05-15 | Gari (white) - Wholesale | 100 KG | cereals and tubers | 11148.0 | NGN | Nigeria | Zamfara | 65710 | Kaura Namoda | 1977.0 | 483 | 14.0 | 9.0 | 1 | 1977_483_14_9 | NaN |
| 13277 | 2018-01-15 | Gari (white) - Retail | KG | cereals and tubers | 165.913 | NGN | Nigeria | Zamfara | 65710 | Kaura Namoda | 1977.0 | 483 | 15.0 | 5.0 | 1 | 1977_483_15_5 | NaN |
13278 rows × 17 columns
The Data set above is a sample of individual types of foods in all 36 Nigerian states between 2002 and 2018. This data has 17 columns; however the important columns are the date, food name, its category of food, the unit (in KG) the price (in Naira), and the state in Nigeria we are looking at. In this project, we will only be use these columns
The 36 states we are looking at are: Abia, Adamawa, Akwa Ibom, Anambra, Bauchi, Bayelsa, Benue, Borno, Cross River, Delta, Ebonyi, Edo, Ekiti, Enugu, Gombe, Imo, Jigawa, Kaduna, Kano, Katsina, Kebbi, Kogi, Kwara, Lagos, Nasarawa, Niger, Ogun, Ondo, Osun, Oyo, Plateau, Rivers, Sokoto, Taraba, Yobe, Zamfara
Food names: Beans, Bread, Cowpeas (brown), Cowpeas (white), Fuel (diseal), Fues (gasoline), Garri (white), Garri (yellow), Groundnuts, Maize, Millet, Palm Oil, Rice (local), Rice (imported), Sorghum, and Yam
The different food categories are: Cereal and Tubers, Oil and Fats, Pulses and Nuts, and non-food
The data is very thorough and well-organized , so there should not be too many issues with the data. However, because there are a lot of columns not being used in the data, it could potentially be overwhelming to work through, but it gives the data a fuller picture.
This data will be combined and potentially sorted by the specigfic food type of the years. price comparison for each age group will be displayed graphically in comparison to the previous year. This representation willdepict the growing prices in every food group over the years. This will allow us to compare how each food group has increased in price over the years and potentially make a suggestion to lower income individuals on which foods they should purchase or potentially even invest in.