Philippines Family Income: Total: Expenditure Class (EC): Ann: Under PhP 40,000 data was reported at 18,200,000.000 PHP th in 2015. This records a decrease from the previous number of 26,928,000.000 PHP th for 2012. Philippines Family Income: Total: Expenditure Class (EC): Ann: Under PhP 40,000 data is updated yearly, averaging 22,564,000.000 PHP th from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 26,928,000.000 PHP th in 2012 and a record low of 18,200,000.000 PHP th in 2015. Philippines Family Income: Total: Expenditure Class (EC): Ann: Under PhP 40,000 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H017: Family Income and Expenditure Survey: Total Annual Income and Expenditure: By Expenditure Class.

's Number of lower secondary school classes (Private) is 685[class] which is the 2nd highest in Japan (by Prefecture). Transition Graphs and Comparison chart between Kanagawa and Tokyo(Tokyo) and Osaka(Osaka)(Closest Prefecture in Population) are available. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

Ave Family Income: EC: Philippines: PhP 100,000 - 249,999 data was reported at 193,000.000 PHP in 2015. This records an increase from the previous number of 188,000.000 PHP for 2012. Ave Family Income: EC: Philippines: PhP 100,000 - 249,999 data is updated yearly, averaging 190,500.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 193,000.000 PHP in 2015 and a record low of 188,000.000 PHP in 2012. Ave Family Income: EC: Philippines: PhP 100,000 - 249,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H019: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Expenditure Class.

's Number of elementary school classes (Special classes, public)is 563[class] which is the 32nd highest in Japan (by Prefecture). Transition Graphs and Comparison chart between Aomori and Nara(Nara) and Iwate(Iwate)(Closest Prefecture in Population) are available. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

's Number of lower secondary school classes (Special classes, public) is 402[class] which is the 16th highest in Japan (by Prefecture). Transition Graphs and Comparison chart between Miyagi and Kyoto(Kyoto) and Niigata(Niigata)(Closest Prefecture in Population) are available. Various data can be downloaded and output in csv format for use in EXCEL free of charge.

A document is any kind of recorded text, in whatever format and in whatever medium; any uniquely identifiable (and hence, separately searchable) part of a larger document; a textual description of a document, such as a catalogue entry or an abstract; any uniquely identifiable part of a description, such as the title field; a title or description of any non-textual item (a picture, a museum object, a video, a program, a data table, etc); and no doubt more. A subject is a summary indication, on the one hand, of what a document is "about", and on the other hand, of what a searcher is "interested" in. Document retrieval (by subject) is the act of finding a document on a particular subject in a collection that is held in a store - that may be a library, an archive, a database, the Internet. How do we find documents in a store? One way is to select separately searchable portions of the text of the document (e.g. the title of a book or chapter or section, or a caption or table heading, etc, or indeed every word in the document) and to treat them as "the subject(s)" of the document: a search mechanism seeking a particular subject then in some way scans the document collection in the store to find documents containing that subject. Alternatively, externally created subject markers can be assigned and added to each document, and be sought by the search mechanism. A subject marker is a combination of words, phrases, or other symbols (let us call each of these a "term") intended to express what the document is "about". Normally the decisions on what the document is about, and on the terms to be used to express this, are made humanly (I will not discuss machine assignation of subject markers). For a given document store, the set of terms chosen to figure in subject markers may be called its term list. For convenient use by indexer and searcher, the term list may be displayed in some ordered sequence (e.g. as a thesaurus). A classification is a term list displayed in some kind of structured form, initially a hierarchy based on the generic, class-inclusion relation, but subsequently more complex. This paper will discuss the form(s) of classification - and, more particularly, of general classifications of wide scope, intended for use by many document stores. The stimulus for this discussion has come from interaction with Claudio Gnoli and his work.

Philippines PTE: PhP 100,000 - 249,999: Education data was reported at 2.500 % in 2015. This records a decrease from the previous number of 2.600 % for 2012. Philippines PTE: PhP 100,000 - 249,999: Education data is updated yearly, averaging 2.550 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 2.600 % in 2012 and a record low of 2.500 % in 2015. Philippines PTE: PhP 100,000 - 249,999: Education data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Will PHP Ventures Acquisition Corp. (PPHP) Class A Stock Bounce Back?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Online Service für Wasserstandsüberwachung in den USA, CA, BE, NL, UK, IE, DE, AT, CH und Südtirol.

Ave Family Income: IC: Philippines: PhP 40,000 - 59,999 data was reported at 51,000.000 PHP in 2015. This stayed constant from the previous number of 51,000.000 PHP for 2012. Ave Family Income: IC: Philippines: PhP 40,000 - 59,999 data is updated yearly, averaging 51,000.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 51,000.000 PHP in 2015 and a record low of 51,000.000 PHP in 2015. Ave Family Income: IC: Philippines: PhP 40,000 - 59,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H018: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Income Class.

Data is taken from Thesis Information Systems (SIM TA) Website of the ITS Information Systems Department (Link: http://is.its.ac.id/apps/simta/simta_mhslist.php). SIM TA's data is used for data collection of ITS Information Systems's students who have proposed the thesis title. In this dataset there are six attribute columns. The first one contains the Student NRP attribute which is the student ID number that applies at ITS. Student NRP contains 14 digit numbers where the first 2 digit numbers indicate the faculty code, the second 2 digit numbers indicate the department code, and the third 2 digit numbers indicate the year class. The second attribute contains the Name of the Student. The third attribute is the Name of the Supervisor of the student's thesis. Fourth attribute is the Thesis Title. The fifth attribute is Lab chosen by students. The last attribute is the Date the Proposal was presented. This dataset is only part of the original data, this data contains 120 rows.

Philippines Family Income: Total: IC: Annual: PhP 60,000 - 99,999 data was reported at 266,410,000.000 PHP th in 2015. This records a decrease from the previous number of 325,936,000.000 PHP th for 2012. Philippines Family Income: Total: IC: Annual: PhP 60,000 - 99,999 data is updated yearly, averaging 296,173,000.000 PHP th from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 325,936,000.000 PHP th in 2012 and a record low of 266,410,000.000 PHP th in 2015. Philippines Family Income: Total: IC: Annual: PhP 60,000 - 99,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H016: Family Income and Expenditure Survey: Total Annual Income and Expenditure: By Income Class.

Abstract

The Department of Census and Statistics continues to conduct the Annual Survey of Industries which commenced in 1984, replacing the Annual Survey of Manufacturing Industries and covers all activities categorized under the three industrial divisions, namely : Mining & Quarrying, Manufacturing and Distribution of Electricity, Gas and Water.

This survey helps to derive estimates for important industrial indicators in respect of all the industrial establishments that have been included in the register of industrial establishments for the year 1992.

Information had to be adjusted for non-responding establishments and the sample data inflated.

The Objectives of the Annual Survey of Industries are:

1. To provide indicators of the performance and the structure of the industrial sector.
2. To update the list of industrial establishments already available.

Geographic coverage

National coverage

Analysis unit

Industrial establishments

Statistical unit of ASI is the establishment which is defined as a unit engaged in the single or related activities of Mining and Quarrying, Manufacturing and Generation and Distribution of Electricity, Gas and Water in one location under a single ownership or control. However, industrial enterprises which are engaged in production of more than one related activity in one location or one activity in several locations were treated as one unit of enumeration whenever no separate records are available. Any way in the analysis, the ideal definition of the establishment was followed. The information collected of enterprise level was disaggregated into establishment level using the proportion of output. Ancillary units such as warehouses, garages, etc were treated as part of the main establishments.

Universe

All industrial establishments where five or more persons are engaged.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Procedure

ASI is predominantly a postal survey . But Statistical Officers are send to the non responding establishments to get the questionnaires completed.

All industrial establishments with 5 or more persons engaged is the target population of ASI. The list of industries with 5 or more persons as in the Census of Industry - 1983 was the frame ( sample population ) of ASI.

The whole frame was divided into two sectors as establishments with 25 or more persons engaged and establishments with 5-24 persons engaged. All establishments in the 25 or more sector ( census part ) and probability sample of 5 to 24 sector (survey part ) were canvassed. The census part of the frame updated from time to time and the survey part remained unchanged.

The survey part was further stratified according to the geographical locations, industrial activity and size. Geographical strata were 24 administrative districts. Industrial activities were defined as the industry group levels (4 digit level of ISIC]. The persons engaged size classes which were defined as 5-9, 10-14 and 15-24 persons engaged, were used as the size strata.

There were approximately 2500 establishments in the census part and approximately another 2500 were selected for the sample out of about 12000 industries. Higher probabilities were given to select rare industries. The sample was selected systematically within the strata.

The estimated value of a variable was given by (pl see the report Sample design section)

           Y(hat) = (Sigma i=1 to 24[Sigma j=1 to 84[Sigma k=1 to 3 Nijk Yijk
                                                         ------
                                                         nijk
                           Where N = total no of units in the population
                                 n = number of units responded
                                 k = size class of persons engaged
                                 j  = industry group of ISIC
                                 i = District

Mode of data collection

Mail Questionnaire [mail]

Research instrument

There were 18 questions in the questionnaire. The first 12 questions were on identification information. Questions 13-16 were on inputs and output and question number 17 and 18 were about the investment and labor of the establishments.

The value of goods moved out, receipt of industrial services done for others and opening and closing stocks of output were collected to compile the gross output.

Inputs were the addition of value of raw materials consumed of the year 1991. (i.e. Cost of raw materials adjusted for stocks ) and the consumption of electricity, fuel and water. Book value at the beginning of the year, gross additions during the year, and Depreciation were canvassed under the four components of fixed assets namely, Land, Building and Other Constructions, Machinery and Other Equipment and Transport Equipment.

The information on employment and earnings, was collected under two sub categories National and Non-Nationals. The number of mail and female national persons engaged were collected separately, but salaries were canvassed only for the total number of employees. In addition to the above non-national employees and their salaries also were canvassed.

Further information extracted from the report : -

Output Information on output has been collected on shipment basis. The variables canvassed were the value of products moved out from the establishment, value of stocks of finished goods and receipts from industrial services rendered to others.

a. Value of products moved out i. Value of products made by the establishment using its own raw materials. ii. Products made by another establishment using material inputs owned by the establishment, have been considered, as the products made by the establishment and the following three situations have been considered as the moving out. i. sending to another establishment or a person ii. sending to another branch of the same enterprise iii. sending abroad

These products were valued at the price at which the producer disposes of his goods to the customer (i.e. producer's price). All duties and taxes which fell on the products when they leave the establishment are included and subsidies recovered are excluded. Price rebates, discounts and allowances on returned goods allowed to the customer have been deducted and any transport charges which may be invoiced to the purchaser or user have been excluded. Products released to other establishments of the same enterprise have been treated as though sold and valued at producer's prices.

b. Stocks of finished goods The values of stocks of finished goods at the beginning and at the end of the year 1991 have been collected. This consists of all finished goods made by the establishment using their own raw materials and manufactured by another establishment using raw materials owned by this establishment and ready for release. Finished goods held by the establishment which were made from materials owned by others have been excluded. Valuation is in producer's prices.

c. Receipts from Industrial Services The total value of receipts from i. Contract and Commission work done for others on materials owned by them, ii. Repairs and installation work done for others, iii. Sales of scraps and refuses, iv. Own account investment work, have been included here.

d. Value of output The value of output was obtained from the value of shipments and other receipts of Industrial Services adjusted for changes in the values of stocks of finished goods during the reference period. Value of Output = (Value of products moved out) + (Closing stocks of finished goods) - (Opening stocks of finished goods) + (Receipts from Industrial Services)

Inputs Information on inputs has been collected covering the costs of a. Raw materials, parts and components and packing materials (Imported and Indigenous) consumed, b. Industrial services done by others for the establishment, c. Fuel, Electricity & Water consumed.

a. Cost of raw materials, parts and components and packing materials i. Cost of raw materials, packing materials purchased All material inputs ( Raw materials, parts, components containers and supplies) purchased by the establishment for the production process either in this establishment or in another establishment have been included. All materials have been valued at purchaser's prices. ie. The delivered value at the establishment, including the purchase price transport charges, cost of insurance, all taxes and duties on the goods. Discounts or rebates allowed to the purchaser and the value of packing materials returned to the supplier have been deducted. The value of materials owned by others and received by the establishment for production process have been excluded and material inputs received by the establishment from other establishments of the same enterprise (not purchased) for processing have been valued as if purchased. ii. Values of stocks of raw materials and packing materials etc. The opening and closing stocks of all input materials (imported and indigenous) including packing materials which are purchased (or treated as purchased) have been included. The valuation was at purchaser's prices. The stocks of raw material used for own account work for producing own fixed assets have been excluded.

b. Cost of industrial services done by others The total cost of i. Contract and commission work done by others on materials supplied by the

Philippines Family Expenditure: Total: IC: Annual: PhP 100,000 - 249,999 data was reported at 1,500,018,000.000 PHP th in 2015. This records an increase from the previous number of 1,307,091,000.000 PHP th for 2012. Philippines Family Expenditure: Total: IC: Annual: PhP 100,000 - 249,999 data is updated yearly, averaging 1,403,554,500.000 PHP th from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 1,500,018,000.000 PHP th in 2015 and a record low of 1,307,091,000.000 PHP th in 2012. Philippines Family Expenditure: Total: IC: Annual: PhP 100,000 - 249,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H016: Family Income and Expenditure Survey: Total Annual Income and Expenditure: By Income Class.

Philippines PTE: PhP 40,000 - 59,999: Health data was reported at 2.200 % in 2015. This records an increase from the previous number of 1.800 % for 2012. Philippines PTE: PhP 40,000 - 59,999: Health data is updated yearly, averaging 2.000 % from Dec 2012 to 2015, with 2 observations. The data reached an all-time high of 2.200 % in 2015 and a record low of 1.800 % in 2012. Philippines PTE: PhP 40,000 - 59,999: Health data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Ave Family Exp: EC: Philippines: PhP 60,000 - 99,999 data was reported at 82,000.000 PHP in 2015. This records an increase from the previous number of 80,000.000 PHP for 2012. Ave Family Exp: EC: Philippines: PhP 60,000 - 99,999 data is updated yearly, averaging 81,000.000 PHP from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 82,000.000 PHP in 2015 and a record low of 80,000.000 PHP in 2012. Ave Family Exp: EC: Philippines: PhP 60,000 - 99,999 data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H019: Family Income and Expenditure Survey: Average Annual Income and Expenditure: By Expenditure Class.

Philippines PTE: PhP 40,000 - 59,999: Other Expenditure data was reported at 0.700 % in 2015. This records a decrease from the previous number of 0.800 % for 2012. Philippines PTE: PhP 40,000 - 59,999: Other Expenditure data is updated yearly, averaging 0.750 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 0.800 % in 2012 and a record low of 0.700 % in 2015. Philippines PTE: PhP 40,000 - 59,999: Other Expenditure data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.

Philippines PTE: Under PhP 40,000: Communication data was reported at 0.300 % in 2015. This records a decrease from the previous number of 0.400 % for 2012. Philippines PTE: Under PhP 40,000: Communication data is updated yearly, averaging 0.350 % from Dec 2012 (Median) to 2015, with 2 observations. The data reached an all-time high of 0.400 % in 2012 and a record low of 0.300 % in 2015. Philippines PTE: Under PhP 40,000: Communication data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.H026: Family Income and Expenditure Survey: Percentage Distribution of Family Expenditure: By Income Class.