cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/ddx28g
title: Genomic data: Nutritional and Biochemical Diversity in Bean Accessions from Three Phaseolus Species Using Multi-Omics Characterization

description: Beans (Phaseolus spp.) are vital food crops, providing essential nutrients and playing a crucial role in global food security. This study presents a multi-omics characterization of 46 accessions from Phaseolus vulgaris (n=35), P. lunatus (n=7), and P. acutifolius (n=4), selected for their morphological diversity from the Future Seeds Genebank. We analyzed their biochemical composition to assess nutritional quality and adaptive traits using proteomics, metabolomics, fatty acid profiling (FAMEs), and ionomics. Proteomic analysis identified over 11,000 unique proteins, with P. vulgaris exhibiting notable diversity. Essential amino acid content varied among species, with P. lunatus showing distinct profiles. Network analysis revealed conserved metabolic pathways and stress-response proteins across species. Metabolomic profiling detected 6,717 metabolites, with flavonoids, polyphenols, and terpenoids predominating. P. lunatus displayed showed a substantial number of unique metabolites, while P. acutifolius exhibited a more conserved metabolic profile, likely linked to its drought tolerance. Fatty acid profiling confirmed a predominance of unsaturated fatty acids, with notable omega-3 content and a favorable omega-6/omega-3 ratio observed in P. vulgaris, suggesting potential health benefits. Ionomic analysis revealed statistically significant variations in mineral composition, with some accessions exhibiting elevated calcium, iron, or zinc levels. One P. vulgaris accession showed concerning levels of lead and cadmium, highlighting the need for further monitoring. This study provides critical insights into Phaseolus species'' nutritional and biochemical diversity, informing health, nutrition sciences and also breeding programs aimed at enhancing food quality, stress resilience, and sustainable crop production. The genotypic data was used to explore the genetic diversity of the nutritionally characterized materials.
&lt;br&gt;
&lt;br&gt; 
Methodology:Genomic DNA was extracted from pooled young leaf tissue of 25 individuals per accession following Correa et al., (2024). DNA from 43 of 46 accessions was processed, excluding accession G7309 and cultivars KATB1 and PALOMINO. Samples were genotyped with DArTseq at medium sequencing density (~1.25 million reads/sample). DNA was digested with PstI and MseI enzymes, and libraries were sequenced on an Illumina NovaSeq 6000. SNP calling was performed de novo using DArT’s DS14 software, aligning reads with a 2–3 nucleotide mismatch threshold. SNPs were assessed for read depth, call rate, reproducibility, and minor allele frequency (maf).
DOI: 10.25549/satjrnl-m5
title: Adskaia pochta, no. 1 (1906)

description: [description (english with transliteration)] Adskaia pochta [Hellish Post], no. 1, [May] 1906. Published by E. E. Lansere. Edited by P. N. Troianskii. St. Petersburg. Тypography: Тоvarishchestvo [Company] R. Golike and A. Vil'borg. Journal of political satire. This issue contains poetry, prose, pictures and illustrations by artists and writers, such as Boris Anisfel'd, Dmitrii Stelletskii, Evgenii Lansere, Maksim Gor'kii and Valerii Briusov -- Rudzinskii, no. 1; BPIR, no. 23.; Artists: B.I. Anisfel'd, L.S. Bakst, Aleks. Benois, I.Ia. Bilibin, I.I. Brodskii, Aksel Gallen (Finland), P. Galonen (Finland), A.F. Gaush, I.E. Grabar', Z.I. Grzhebin, M.D. Erro Ernefel'd (Finland), A. Zal'tsman, S.V. Ivanov, D.N. Kardovskii, E.S. Kruglikova, B.M. Kustodiev, E.E. Lansere, M.P. Latri, V.N. Levitskii, A. Liubimov, E.K. Makovskaia, V.D. Milioti, N.D. Milioti, A.P. Ostroumova, L.O. Pasternak, I. Plekhanov, I. Rissanen (Finland), Iu.I. Repin, Saarinen (Finland), K.A. Somov, D.S. Stelletskii, V.A. Serov, P.N. Troianskii, V.Ia. Chembers, M.Ch., P.I. Shcherbov, K.F. Iuon.; Writers: Allegro, A. Amfiteatrov, L. Andreev, M.P. Artsybashev, K.D. Bal'mont, A. Blok, V. Briusov, A. Bely, I. Bunin, Galich, M. Gor'kii, S. Gusev-Orenburgskii, O. Dymov, V. Zhabotinskii, B. Zaitsev, L. Zinov'eva-Annibal, Viach. Ivanov, V.V. Karrik, N. Krandievskaia, A.I. Kuprin, A.B. Petrishchev, S.L. Poliakov, Pek, A.M. Remizov, Silen, Skitalets, F. Sologub, Teffi, D.V. Filosofov, E.N. Chirikov, K. Chukovskii, G. Chulkov, K. Erberg and A.A. Iablonovskii. Contributors from the journal "Simplicissimus" -T.T. Heine, Bruno Paul, R. Wilke, O. Gulbranson.
DOI: 10.5281/zenodo.18805954
title: CURRENT ISSUES OF LITERARY SPEECH STYLISTICS AND TRANSLATION STUDIES

description:  The article provides information about the Uzbek language and its speech styles, the innovations in linguistics and literature that have emerged through them, as well as the role of speech styles in translation studies. In addition, the article comments on the role and level of translation studies in the development of the Uzbek language. Along with this, the book “Annotated dictionary of onomastic units used in the Nasimi language” by the Azerbaijani scientist Khadicha Haydarova, which was recently translated as one of the examples of translation studies, and the research conducted during the translation process were discussed. It should also be noted that this article also contains conclusions and suggestions regarding some issues in business science.
DOI: 10.15468/dl.cfaar9
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Material sample, Material citation, Specimen)",
 "Country is Peru",
 "TaxonKey is Ateles belzebuth"
 ]
}

 The dataset includes 62 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002710-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18805953
title: CURRENT ISSUES OF LITERARY SPEECH STYLISTICS AND TRANSLATION STUDIES

description:  The article provides information about the Uzbek language and its speech styles, the innovations in linguistics and literature that have emerged through them, as well as the role of speech styles in translation studies. In addition, the article comments on the role and level of translation studies in the development of the Uzbek language. Along with this, the book “Annotated dictionary of onomastic units used in the Nasimi language” by the Azerbaijani scientist Khadicha Haydarova, which was recently translated as one of the examples of translation studies, and the research conducted during the translation process were discussed. It should also be noted that this article also contains conclusions and suggestions regarding some issues in business science.
DOI: 10.3886/e205981v1-199750
title: Code for `Eliminating Fares to Expand Opportunities: Experimental Evidence on the Impacts of Free Public Transportation on Economic and Social Disparities'

description: This package includes code and some data to replicate the paper. All code is included. Some data in not included due to legal limitations on data sharing.<br><br>Abstract: We conduct a randomized controlled trial to study the employment effects of providing free public transportation to individuals with low income. A temporary subsidy that reduces the price of transit to zero has no significant effects on individuals' paid hours worked or earnings. Using rich administrative data, we also explore a range of other outcomes. We find suggestive evidence that transit subsidies improve measures of financial and physical health.
description: People visiting public benefit offices in King County Washington who participated in a randomized controlled trial.
DOI: 10.15468/dl.z7tskg
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Tragiella"
 ]
}

 The dataset includes 88 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002711-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3wu9a8
title: Occurrence Download

description: A dataset containing 164357 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The Himalayan Uplands Plant database (HUP Version 1)"
 ]
}

 The dataset includes 164357 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002702-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25824/redu/negkhg
title: DFT single point calculations for the g3/05 test set

description: Single point calculations using DFT for the molecules present in the G3/05 test set. These calculations were used to train AI models to predict the best functional to be used in the determination of heats of formation using DFT.
DOI: 10.15468/dl.4xhhk9
title: Occurrence Download

description: A dataset containing 2055 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Campomanesia pubescens",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 2055 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002712-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gu9taq
title: Occurrence Download

description: A dataset containing 323159 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-99.26692 18.84895,-98.9325 18.84895,-98.9325 19.10002,-99.26692 19.10002,-99.26692 18.84895))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 323159 records from 550 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002680-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/lachs-c76-1132
title: LACHS newsletter, v. [31], n. 4 (2010-11)

description: Los Angeles City Historical Society newsletter, vol. 42 [sic, i.e. 31], no. 4 (2010 November).
DOI: 10.18131/ngerj-6bp65
title: Supplementary Data for: The Transcription Factor TCF21 is Necessary for Adoption of Cell Fates by Foxd1+ Stromal Progenitors during Kidney Development

description: Supplementary Materials

Supplementary Figure Legends

Supplementary Methods

Suppl Fig. S1: Flow cytometry analysis of single-cell suspensions from E14.5 mouse kidneys for scRNA-seq

Suppl Fig. S2: Single-cell RNA-seq analysis of Foxd1GFP+ sorted cells from control and Tcf21-cKO kidneys

Suppl Fig. S3: Single-cell RNA-seq analysis of stromal cells

Suppl Fig. S4: Stromal subpopulation markers for module scores 

Suppl Fig. S5: Comparison of stromal cells between Tcf21-cKO and controls

Suppl Fig. S6: Elbow plot, cluster tree, and proportion graph by sex for stromal clusters

Suppl Fig. S7: Stromal Endomucin+ cells in E18.5 Tcf21-cKO kidneys

Suppl Fig. S8: Single-cell RNA-seq analysis of E18.5 control and Tcf21-cKO kidneys

Suppl Fig. S9: Lineage annotation of single-cell ATAC-seq analysis at E14.5

Suppl Table S1: E14.5 scRNA-seq a. All cluster markers.  b. Cell type markers

Suppl Table S2: E14.5 scRNA-seq a. Stromal subpopulation markers. b. Marker overlap with Combes et al

Suppl Table S3: E14.5 scRNA-seq a. Downsampled cell numbers by stromal cluster by sample b. Differential gene expression output c. GO term output up-regulated d. GO term output down-regulated

Suppl Table S4: a. Monocle module genes. b. Number of cells expressing modules

Suppl Table S5: E18.5 scRNA-seq a. All cluster markers b. Stromal subpopulation markers c. Emcn+ mutant markers

Suppl Table S6: Matrisome associated gene module

Suppl Table S7: E14.5 scATAC-seq a. Stromal subpopulation markers based on gene activity scores

Suppl Table S8: E18.5 bulk RNA-seq a. DEGs (Tcf21-cKO vs Control) b. GO Term up-regulated c. GO Term down-regulated

Suppl Table S9: Significant ligand-receptor interactions from CellChat
DOI: 10.25549/lachs-c76-1446
title: LACHS newsletter, v. [32], n. 1 (2011-02)

description: Los Angeles City Historical Society newsletter, vol. 44 [sic, i.e. 32], no. 1 (2011 February).
DOI: 10.25549/lachs-c76-1455
title: LACHS newsletter, v. [32], n. 1 (2011-02)

description: Los Angeles City Historical Society newsletter, vol. 44 [sic, i.e. 32], no. 1 (2011 February).
DOI: 10.25549/lachs-c76-1457
title: LACHS newsletter, v. [32], n. 1 (2011-02)

description: Los Angeles City Historical Society newsletter, vol. 44 [sic, i.e. 32], no. 1 (2011 February).
DOI: 10.25549/lachs-c76-1145
title: LACHS newsletter, v. [32], n. 2 (2011-05)

description: Los Angeles City Historical Society newsletter, vol. 44 [sic, i.e. 32], no. 2 (2011 May).
DOI: 10.25549/satjrnl-ouc112744969
title: Adskaia pochta, no. 1 (1906)

description: [description (english with transliteration)] Adskaia pochta [Hellish Post], no. 1, [May] 1906. Published by E. E. Lansere. Edited by P. N. Troianskii. St. Petersburg. Тypography: Тоvarishchestvo [Company] R. Golike and A. Vil'borg. Journal of political satire. This issue contains poetry, prose, pictures and illustrations by artists and writers, such as Boris Anisfel'd, Dmitrii Stelletskii, Evgenii Lansere, Maksim Gor'kii and Valerii Briusov -- Rudzinskii, no. 1; BPIR, no. 23.; Artists: B.I. Anisfel'd, L.S. Bakst, Aleks. Benois, I.Ia. Bilibin, I.I. Brodskii, Aksel Gallen (Finland), P. Galonen (Finland), A.F. Gaush, I.E. Grabar', Z.I. Grzhebin, M.D. Erro Ernefel'd (Finland), A. Zal'tsman, S.V. Ivanov, D.N. Kardovskii, E.S. Kruglikova, B.M. Kustodiev, E.E. Lansere, M.P. Latri, V.N. Levitskii, A. Liubimov, E.K. Makovskaia, V.D. Milioti, N.D. Milioti, A.P. Ostroumova, L.O. Pasternak, I. Plekhanov, I. Rissanen (Finland), Iu.I. Repin, Saarinen (Finland), K.A. Somov, D.S. Stelletskii, V.A. Serov, P.N. Troianskii, V.Ia. Chembers, M.Ch., P.I. Shcherbov, K.F. Iuon.; Writers: Allegro, A. Amfiteatrov, L. Andreev, M.P. Artsybashev, K.D. Bal'mont, A. Blok, V. Briusov, A. Bely, I. Bunin, Galich, M. Gor'kii, S. Gusev-Orenburgskii, O. Dymov, V. Zhabotinskii, B. Zaitsev, L. Zinov'eva-Annibal, Viach. Ivanov, V.V. Karrik, N. Krandievskaia, A.I. Kuprin, A.B. Petrishchev, S.L. Poliakov, Pek, A.M. Remizov, Silen, Skitalets, F. Sologub, Teffi, D.V. Filosofov, E.N. Chirikov, K. Chukovskii, G. Chulkov, K. Erberg and A.A. Iablonovskii. Contributors from the journal "Simplicissimus" -T.T. Heine, Bruno Paul, R. Wilke, O. Gulbranson.
DOI: 10.34804/supra.20210928332
title: Excited state proton transfer of pyranine in a γ-cyclodextrin cavity

description: null
DOI: 10.15468/dl.6jrm58
title: Occurrence Download

description: A dataset containing 112 records in GBIF matching the query:

SELECT
 GBIF_ISEA3HCode(
 8, 
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)
 ) AS geogrid_id,
 CASE 
 WHEN classKey IN ('359') THEN 'Mammals'
 WHEN classKey IN ('212') THEN 'Birds'
 WHEN familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879') THEN 'Bony Fish'
 WHEN classKey IN ('131') THEN 'Amphibians'
 WHEN classKey IN ('216') THEN 'Insects'
 WHEN classKey IN ('11418114', '11569602', '11592253', '11493978') THEN 'Reptiles'
 WHEN phylumKey IN ('52') THEN 'Molluscs'
 WHEN classKey IN ('367') THEN 'Arachnids'
 WHEN classKey IN ('220', '196') THEN 'Flowering Plants'
 WHEN classKey IN ('194', '244', '228', '282') THEN 'Gymnosperms'
 WHEN orderKey IN ('392') THEN 'Ferns'
 WHEN phylumKey IN ('35') THEN 'Mosses'
 WHEN phylumKey IN ('95') THEN 'Sac Fungi'
 WHEN phylumKey IN ('34') THEN 'Basidiomycota'
 END AS taxonomic_group,
 COUNT(DISTINCT speciesKey) AS species_count
FROM occurrence
WHERE countryCode = 'KP'
 AND hasCoordinate = TRUE
 AND hasGeospatialIssues = FALSE
 AND coordinateUncertaintyInMeters &lt;= 2000
 AND occurrenceStatus = 'PRESENT'
 AND speciesKey IS NOT NULL
 AND basisOfRecord != 'FOSSIL_SPECIMEN'
 AND taxonRank = 'SPECIES'
 AND (
 classKey IN ('359', '212', '131', '216', '11418114', '11569602', '11592253', '11493978', '367', '220', '196', '194', '244', '228', '282')
 OR familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879')
 OR phylumKey IN ('52', '35', '95', '34')
 OR orderKey IN ('392')
 )
GROUP BY geogrid_id, taxonomic_group;


 The dataset's 112 records were derived from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002706-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/satjrnl-m121
title: Adskaia pochta, vol. 1, no. 3 (1906-06)

description: [description (english with transliteration)] Adskaia pochta [Hellish Post], no. 3, June 1906. Published by E. E. Lansere. Edited by P. N. Troianskii. St. Petersburg. Тypography: "Tovarishchestvo [Company] R. Golike and A. Vil'borg." Journal of political satire -- Rudzinskii, no. 1; BPIR, no. 23.; Artists and writers: Leonid Andreev, I. Bilibin, M. Gor'kii, Z. Grzhebin, M. Dobuzhinskii, O. Dymov, Viach. Ivanov, D. Kardovskii, A. Kuprin, E. Lansere, Silen, K. Somov, V. Serov, and G. Chulkov release the journal "Adskaia pochta." Contributors from the journal "Simplicissimus" -T.T. Heine, Bruno Paul, R. Vilke, O. Gulbranson.
DOI: 10.6084/m9.figshare.30813941
title: Raw metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction

description: Raw metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction. Companion dataset to DOI: --placeholder--Contains raw files (.raw Thermo format) for both ionization modes.<br><br>Control n = 30DCI n = 30Phenotype alignment for 24-48h and 48-72h time buckets before DCI onset.
DOI: 10.6084/m9.figshare.30813941.v1
title: Raw metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction

description: Raw metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction. Companion dataset to DOI: --placeholder--Contains raw files (.raw Thermo format) for both ionization modes.<br><br>Control n = 30DCI n = 30Phenotype alignment for 24-48h and 48-72h time buckets before DCI onset.
DOI: 10.6084/m9.figshare.30813929
title: Processed metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction

description: Processed metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction. Companion dataset to DOI: --placeholder--Contains two data matrices: 2,022 annotated compounds .csv file<br>9,035 unannotated + annotated compounds .csv file <br>Control n = 30DCI n = 30Phenotype alignment for 24-48h and 48-72h time buckets before DCI onset.
DOI: 10.6084/m9.figshare.30813929.v1
title: Processed metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction

description: Processed metabolomics data of 60 phenotype-aligned post-aSAH patients for DCI prediction. Companion dataset to DOI: --placeholder--Contains two data matrices: 2,022 annotated compounds .csv file<br>9,035 unannotated + annotated compounds .csv file <br>Control n = 30DCI n = 30Phenotype alignment for 24-48h and 48-72h time buckets before DCI onset.
DOI: 10.5281/zenodo.18407659
title: ReEDS: Utility-scale PV profiles

description: This record provides modeled hourly utility-scale photovoltaic (PV) capacity factor profiles for the contiguous United States (U.S.), generated using the National Solar Radiation Database (NSRDB), System Advisor Model (SAM), and Renewable Energy Potential (reV) model. These profiles are used in the Regional Energy Deployment System (ReEDS) model.

 

Additional details are provided in the ReEDS documentation.

Technology assumptions

Utility-scale PV capacity factor profiles use assumptions consistent with the 2024 Annual Technology Baseline (ATB) and Lopez et al. (2025) assumptions for 2035, namely:






1-axis tracking with 0° tilt

Inverter loading ratio: 1.34

DC losses: 10.4%

Ground cover ratio: 0.4


Values are given in units of  $[MW_{AC,grid}/MW_{DC,array}]$, where  $MW_{AC,grid}$ is the post-inverter output to the grid and  $MW_{DC,array}$ is the pre-inverter PV array capacity. To convert to units of  $[MW_{AC,grid}/MW_{AC,nameplate}]$, the profiles should be multiplied by the inverter loading ratio of 1.34  $[MW_{DC,array}/MW_{AC,nameplate}]$.

Temporal resolution



All capacity factor profiles are at hourly resolution in U.S. Central Standard Time (UTC–06:00) and represent instantaneous values on the hour. The profiles span 15 weather years (2007–2013 + 2016–2023). For leap years, the final day of the year (December 31) is dropped, such that each year contains 8760 hours.

Spatial resolution



Capacity factor profiles are provided for three siting access assumptions described by Lopez et al. (2025) ("limited", "reference", and "open") and two spatial resolutions. Files with names ending in "county" are resolved for individual U.S. counties; files with names ending in "ba" are resolved for the 134 ReEDS model zones. Profiles are further differentiated into five resource classes, with higher class numbers indicating higher average capacity factor.




 

File structure





county2zone.csv: U.S. counties comprising each of the 134 ReEDS model zones

cf_upv_{access scenario}_{ba or county}.h5: Hourly capacity factor profiles. Columns are labeled as {resource class}|p{zone number or 5-digit county FIPS code}.

sc_upv_{access scenario}_{ba or county}.csv: Available capacity [MW] associated with each class/region capacity factor profile



Capacity factor profiles are saved as hierarchical Data Format (HDF5) files. The following Python function can be used to read a capacity factor .h5 file into a pandas dataframe:

 





import h5py

import pandas as pd


def read_cf_profile(filepath):

    """

    Read a CF profile from `filepath` and return a pandas dataframe.


    Usage:

    `df = read_profile('/path/to/filename.h5')`

    """

    encoding = 'utf-8'

    with h5py.File(filepath, 'r') as f:

        df = pd.DataFrame(

            f['data'][:],

            columns=pd.Series(f['columns']).str.decode(encoding),

            index=f['index_0'],

        )

        df.index = pd.to_datetime(

            pd.Series(df.index, name='datetime').str.decode(encoding)

        )


   return df