Data
Consumer-Price-Index

Consumer-Price-Index

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals. The data refers to group wise all India Consumer Price Index for Rural Urban with base year 2010. The dataset is published by Central Statistical Office and released on 12th of every month.

30 features

Sectorstring3 unique values
0 missing
Yearnumeric8 unique values
0 missing
Monthstring14 unique values
0 missing
Cereals_and_productsnumeric181 unique values
3 missing
Meat_and_fishnumeric206 unique values
6 missing
Eggnumeric201 unique values
3 missing
Milk_and_productsnumeric194 unique values
3 missing
Oils_and_fatsnumeric165 unique values
3 missing
Fruitsnumeric201 unique values
3 missing
Vegetablesnumeric233 unique values
3 missing
Pulses_and_productsnumeric214 unique values
3 missing
Sugar_and_Confectionerynumeric175 unique values
3 missing
Spicesnumeric197 unique values
3 missing
Non-alcoholic_beveragesnumeric182 unique values
3 missing
Prepared_meals,_snacks,_sweets_etc.numeric213 unique values
6 missing
Food_and_beveragesnumeric189 unique values
3 missing
Pan,_tobacco_and_intoxicantsnumeric230 unique values
6 missing
Clothingnumeric211 unique values
6 missing
Footwearnumeric203 unique values
6 missing
Clothing_and_footwearnumeric212 unique values
6 missing
Housingnumeric84 unique values
91 missing
Fuel_and_lightnumeric190 unique values
3 missing
Household_goods_and_servicesnumeric203 unique values
6 missing
Healthnumeric215 unique values
3 missing
Transport_and_communicationnumeric163 unique values
6 missing
Recreation_and_amusementnumeric217 unique values
6 missing
Educationnumeric215 unique values
6 missing
Personal_care_and_effectsnumeric195 unique values
6 missing
Miscellaneousnumeric203 unique values
6 missing
General_indexnumeric203 unique values
6 missing

19 properties

267
Number of instances (rows) of the dataset.
30
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
208
Number of missing values in the dataset.
93
Number of instances with at least one value missing.
28
Number of numeric attributes.
0
Number of nominal attributes.
0.11
Number of attributes divided by the number of instances.
93.33
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
34.83
Percentage of instances having missing values.
Average class difference between consecutive instances.
2.6
Percentage of missing values.

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