Concept: Average interest rate of credit operations with prefixed interest rates by source of funds - small-sized enterprise - nonearmarked credit - foreign onlending Source: Credit Information System 26457-average-interest-rate-by-source-of-funds---small-sized-enterprise---nonearmarked-credit---for 26457-average-interest-rate-by-source-of-funds---small-sized-enterprise---nonearmarked-credit---for 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - small-sized enterprise - nonearmarked credit - Acquired receivables Source: Credit Information System 26578-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 26578-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

The benchmark interest rate in Switzerland was last recorded at 0 percent. This dataset provides - Switzerland Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - small-sized enterprise - nonearmarked credit - Securities financing Source: Credit Information System 26565-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 26565-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - small-sized enterprise - nonearmarked credit - Working capital with maturity of more than 365 days Source: Credit Information System 26547-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 26547-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonear 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

Based on a large historical panel dataset, this paper provides evidence that the government spending multiplier can be significantly higher when interest rates are at or near the zero lower bound (ZLB). We estimate multipliers that are as high as 1.5 during ZLB episodes but small and statistically indistinguishable from zero during normal times. Our results are robust to different definitions of ZLB episodes, alternative ways of identifying government spending shocks, controlling for the exchange rate regime, and other potentially important state variables. In particular, we show that the difference in multipliers is not driven by multipliers being higher during periods of economic slack.

Data Description

1 id : To uniquely identify every loan in the dataset.

2 member_id : To identify the borrower to who has applied for the loan. 3 loan_amnt : The listed amount of the loan applied for by the borrower. 4 funded_amnt : The amount that was sanctioned by the LC. 5 term : The number of payments on the loan. Values are in months and can be either 36 or 60. 6 int_rate : Interest Rate on the loan 7 installment : The monthly payment owed by the borrower if the loan originates. 8 grade : LC assigned loan grade which depends on the borrower’s credit score. 9 sub_grade : LC assigned loan subgrade 10 emp_title : The job title supplied by the Borrower when applying for the loan.* 11 emp_length : Employment length in years. Possible values are between 0 and 10 where 0 means less than one year and 10 means ten or more years. 12 home_ownership : The home ownership status provided by the borrower during registration or obtained from the credit report. Our values are: RENT, OWN, MORTGAGE, OTHER 13 annual_inc : The self-reported annual income provided by the borrower during registration. 14 verification_status : Indicates if income was verified by LC, not verified, or if the income source was verified 15 issue_d : The month which the loan was funded 16 loan_status : Current status of the loan 17 purpose : A category provided in the form of a code to indicate the purpose for the loan. 18 title : Explaining the ‘purpose’ of the loan. 19 dti : The debt to income ratio is the ratio of how much the borrower owes every month to the borrower’s income every month. 20 delinq_2yrs : The number of delinquencies(late installment payment) by the borrower in the past 2 years. 21 earliest_cr_line : The month-year the borrower's earliest reported credit line was opened 22 inq_last_6mths : Inquiries for loans made by the borrower over the past 6 months. 23 mths_since_last_delinq : Months that have passed since the borrower last missed the timely payment of installment. 24 open_acc : The number of open credit lines in the borrower’s credit file. 25 pub_rec Number of derogatory public records 26 revol_bal : Total credit revolving balance 27 revol_util : Revolving line utilization rate, or the amount of credit the borrower is using relative to all available revolving credit. 28 total_acc : The total number of credit lines currently in the borrower's credit file 29 initial_list_status : The initial listing status of the loan. Possible values are – W(whole), F(fractional) 30 out_prncp : Remaining outstanding principal for total amount funded 31 total_pymnt : Payments received to date for the total amount funded. 32 total_rec_prncp : Principal received till date. 33 total_rec_int Interest received till date. 34 total_rec_late_fee : Late fees received to date. 35 recoveries : Total recovery procedures initiated against the borrower. 36 collection_recovery_fee : The fees collected during the recovery procedures. 37 last_pymnt_d The last month when payment was received. 38 last_pymnt_amnt : The last payment amount received. 39 next_pymnt_d : Next scheduled payment date. 40 last_credit_pull_d : The most recent month LC pulled credit for this loan 41 collections_12_mths_ex_med : Number of collections in 12 months excluding medical collections 42 mths_since_last_major_derog : Months since most recent 90-day delinquency or worse rating 43 application_type Indicates whether the loan is an individual application or a joint application with two co-borrowers 44 annual_inc_joint : The combined self-reported annual income provided by the co-borrowers during registration 45 dti_joint : A ratio calculated using the co-borrowers' total monthly payments on the total debt obligations, excluding mortgages and the requested LC loan, divided by the co-borrowers' combined self-reported monthly income 46 acc_now_delinq : The number of accounts on which the borrower is now delinquent 47 tot_coll_amt : Total collection amounts ever owed by the borrower 48 tot_cur_bal : Total current balance of all accounts owned by the borrower 49 total_rev_hi_lim : Total high credit/credit limit

Analysis of ‘ Zillow Housing Aspirations Report’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/zillow-housing-aspirations-reporte on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

Additional Data Products

Product: Zillow Housing Aspirations Report

Date: April 2017

Definitions

Home Types and Housing Stock

• All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.
• Condo/Co-op: Condominium and co-operative homes.
• Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.
• Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Additional Data Products

• Zillow Home Value Forecast (ZHVF): The ZHVF is the one-year forecast of the ZHVI. Our forecast methodology is methodology post.
• Zillow creates our negative equity data using our own data in conjunction with data received through our partnership with TransUnion, a leading credit bureau. We match estimated home values against actual outstanding home-related debt amounts provided by TransUnion. To read more about how we calculate our negative equity metrics, please see our here.
• Cash Buyers: The share of homes in a given area purchased without financing/in cash. To read about how we calculate our cash buyer data, please see our research brief.
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio, Historical ZHVI, Historical ZHVI and Houshold Income are calculated as a part of Zillow’s quarterly Affordability Indices. To calculate mortgage affordability, we first calculate the mortgage payment for the median-valued home in a metropolitan area by using the metro-level Zillow Home Value Index for a given quarter and the 30-year fixed mortgage interest rate during that time period, provided by the Freddie Mac Primary Mortgage Market Survey (based on a 20 percent down payment). Then, we consider what portion of the monthly median household income (U.S. Census) goes toward this monthly mortgage payment. Median household income is available with a lag. For quarters where median income is not available from the U.S. Census Bureau, we calculate future quarters of median household income by estimating it using the Bureau of Labor Statistics’ Employment Cost Index. The affordability forecast is calculated similarly to the current affordability index but uses the one year Zillow Home Value Forecast instead of the current Zillow Home Value Index and a specified interest rate in lieu of PMMS. It also assumes a 20 percent down payment. We calculate rent affordability similarly to mortgage affordability; however we use the Zillow Rent Index, which tracks the monthly median rent in particular geographical regions, to capture rental prices. Rents are chained back in time by using U.S. Census Bureau American Community Survey data from 2006 to the start of the Zillow Rent Index, and Decennial Census for all other years.
• The mortgage rate series is the average mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate mortgage in 15-minute increments during business hours, 6:00 AM to 5:00 PM Pacific. It does not include quotes for jumbo loans, FHA loans, VA loans, loans with mortgage insurance or quotes to consumers with credit scores below 720. Federal holidays are excluded. The jumbo mortgage rate series is the average jumbo mortgage rate quoted on Zillow Mortgages for a 30-year, fixed-rate, jumbo mortgage in one-hour increments during business hours, 6:00 AM to 5:00 PM Pacific Time. It does not include quotes to consumers with credit scores below 720. Traditional federal holidays and hours with insufficient sample sizes are excluded.

About Zillow Data (and Terms of Use Information)

• Zillow is in the process of transitioning some data sources with the goal of producing published data that is more comprehensive, reliable, accurate and timely. As this new data is incorporated, the publication of select metrics may be delayed or temporarily suspended. We look forward to resuming our usual publication schedule for all of our established datasets as soon as possible, and we apologize for any inconvenience. Thank you for your patience and understanding.
• All data accessed and downloaded from this page is free for public use by consumers, media, analysts, academics etc., consistent with our published Terms of Use. Proper and clear attribution of all data to Zillow is required.
• For other data requests or inquiries for Zillow Real Estate Research, contact us here.
• All files are time series unless noted otherwise.
• To download all Zillow metrics for specific levels of geography, click here.
• To download a crosswalk between Zillow regions and federally defined regions for counties and metro areas, click here.
• Unless otherwise noted, all series cover single-family residences, condominiums and co-op homes only.

Source: https://www.zillow.com/research/data/

This dataset was created by Zillow Data and contains around 200 samples along with Unnamed: 1, Unnamed: 0, technical information and other features such as: - Unnamed: 1 - Unnamed: 0 - and more.

How to use this dataset

• Analyze Unnamed: 1 in relation to Unnamed: 0
• Study the influence of Unnamed: 1 on Unnamed: 0
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Zillow Data

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--- Original source retains full ownership of the source dataset ---

View data of the Effective Federal Funds Rate, or the interest rate depository institutions charge each other for overnight loans of funds.

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds - small-sized enterprise - earmarked credit - savings deposits for real estate financing operations Source: Credit Information System 26453-average-interest-rate-by-source-of-funds---small-sized-enterprise---earmarked-credit---saving 26453-average-interest-rate-by-source-of-funds---small-sized-enterprise---earmarked-credit---saving 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

The dataset captures the dynamic fluctuations in the exchange rate between the United States Dollar (USD) and the Pakistani Rupee (PKR) over an extensive period, spanning from February 1992 to November 2023. This dataset is a valuable resource for analysts, economists, and researchers seeking to understand the historical trends, patterns, and factors influencing the USD to PKR exchange rate.

Dataset Overview:

Temporal Range: Start Date: February 1992 End Date: November 2023

Frequency: Daily exchange rates

Data Fields: Date: The date for each recorded exchange rate. USD to PKR Exchange Rate: The exchange rate indicating how much one USD is equivalent to in PKR on a given day. Change: Change between last price and today Price

Key Insights and Potential Analysis Areas:

Trend Analysis: Identify long-term trends in the exchange rate over the entire duration. Highlight periods of stability, volatility, or significant fluctuations.

Seasonal Patterns: Explore if there are any recurring seasonal patterns influencing the exchange rate.

Economic Events: Correlate major economic events, both global and domestic, with corresponding shifts in the exchange rate.

Impact of Policies: Assess the impact of monetary and fiscal policies on the USD to PKR exchange rate.

Currency Market Dynamics: Analyze how market dynamics, including demand and supply forces, influence the exchange rate.

Inflation and Interest Rates: Examine the relationship between inflation rates, interest rates, and the exchange rate.

Potential Applications:

Investment Planning: Assist investors in making informed decisions based on historical exchange rate trends.

Risk Management: Aid businesses in assessing and managing currency risk exposure.

Economic Research: Facilitate research on the impact of economic indicators on exchange rates.

Government Policy Evaluation: Provide insights for policymakers in evaluating the effectiveness of monetary and fiscal policies.

Conclusion:

This comprehensive USD to PKR exchange rate dataset offers a wealth of information for various stakeholders. Whether analyzing market trends, conducting economic research, or making strategic financial decisions, this dataset serves as a valuable tool for understanding the historical dynamics of the USD to PKR exchange rate over more than three decades.

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - small-sized enterprise - earmarked credit - Honored guarantees Source: Credit Information System 27286-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---earmar 27286-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---earmar 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

The benchmark interest rate in Czech Republic was last recorded at 3.50 percent. This dataset provides the latest reported value for - Czech Republic Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The dataset simulates student learning behavior during educational sessions, specifically capturing physiological, emotional, and activity-related data. It integrates data collected from multiple IoT sensors, including wearable devices (for tracking movement and physiological states), cameras (for analyzing facial expressions), and motion sensors (for activity tracking). The dataset contains 1,200 student-session records and is structured to represent diverse learning environments, capturing various engagement levels and emotional states.

Here’s a breakdown of the dataset and its features:

Session_ID:

Unique identifier for each session. Type: Integer Student_ID:

A unique identifier for each student participating in the session. Type: Integer HRV (Heart Rate Variability):

A physiological measure of heart rate variability, indicating the variability between consecutive heartbeats, which can provide insights into stress or engagement levels. Type: Continuous (normalized values) Skin_Temperature:

Skin temperature during the session, used to infer physiological responses to learning (such as stress or excitement). Type: Continuous (normalized values) Expression_Joy:

A feature extracted from facial expression analysis, representing the level of joy detected on the student’s face. Type: Continuous (value between 0 and 1) Expression_Confusion:

A feature extracted from facial expression analysis, representing the level of confusion detected on the student’s face. Type: Continuous (value between 0 and 1) Steps:

The number of steps the student has taken during the session, serving as an indicator of activity level. Type: Integer Emotion:

Categorized emotional state of the student during the session, derived from facial expression and engagement analysis. Values: Interest, Boredom, Confusion, Happiness Type: Categorical Engagement_Level:

A rating scale from 1 to 5 that measures the level of engagement of the student during the session. Type: Integer (1 to 5) Session_Duration:

The total duration of the session in minutes, capturing how long the student was engaged in the learning activity. Type: Integer (15 to 60 minutes) Learning_Phase:

The phase of the learning session (e.g., Introduction, Practice, Conclusion). Values: Introduction, Practice, Conclusion Type: Categorical Start_Time:

The timestamp of when the learning session started. Type: DateTime End_Time:

The timestamp of when the learning session ended. Type: DateTime Learning_Outcome:

The result of the learning session, based on the student's engagement level and session duration. Values: Successful, Unsuccessful, Partially Successful Type: Categorical HRV_Frequency_Feature:

A frequency-domain feature derived from the Fourier Transform of the HRV signal, capturing periodic fluctuations in heart rate during the session. Type: Continuous Skin_Temperature_Frequency_Feature:

A frequency-domain feature derived from the Fourier Transform of the skin temperature signal, capturing periodic variations in temperature. Type: Continuous Emotion_Label:

A numeric label corresponding to the Emotion column, used for machine learning model training. Values: 0 to 3 (corresponding to Interest, Boredom, Confusion, Happiness) Type: Integer Learning_Phase_Label:

A numeric label corresponding to the Learning_Phase column, used for machine learning model training. Values: 0 to 2 (corresponding to Introduction, Practice, Conclusion) Type: Integer

Concept: Average interest rate of credit operations with prefixed interest rates by source of funds and type of credit - small-sized enterprise - earmarked credit - Working capital with maturity up to 365 days Source: Credit Information System 27287-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---earmar 27287-average-interest-rate-by-source-of-funds-and-type-of-credit---small-sized-enterprise---earmar 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

Concept: Average interest rate of small-sized enterprises credit operations with prefixed interest rate Source: Credit Information System 26429-average-interest-rate-by-size-of-the-borrower---small-sized-enterprise 26429-average-interest-rate-by-size-of-the-borrower---small-sized-enterprise 0 0 Feedback Thank you! Close Feedback. Sorry. Tell us what happen. The data is out of date. I was unable to access the dataset (specify the resource). Insufficient documentation to understand the data set. The data contains error or inconsistency. Describe Your assessment will be sent to the e-Ouv system as a complaint. Click here if you want to track your progress. Name Email Your statement was sent to the e-Ouv system. Click here for details. Protocol number: Access code: Send to e-Ouv system Close

Inflation Rate in Switzerland decreased to -0.10 percent in May from 0 percent in April of 2025. This dataset provides - Switzerland Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The yield on Portugal 10Y Bond Yield rose to 3.09% on July 2, 2025, marking a 0.07 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.11 points, though it remains 0.11 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Portugal 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.