Atmosfera USM Data Policy

The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.

The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.

Data users who intend to publish research using data must:

Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.

CC-BY-4.0

CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.

Data use should follow these attribution guidelines for CC-BY-4.0:

• Cite the data-collection paper, for example, cite Yusup et al. 2020.
• List the site by its DOI in the paper (these DOIs are provided with the download).

It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.

How to use the data

Converting JSON to DataFrame using jsonlite package in R

# Load the library; ensure that you have installed it first
# install.packages('jsonlite', dependencies=TRUE, repos='http://cran.rstudio.com/')
library(jsonlite)

# Give the input file name to the function. Place the JSON file in the working directory
data <- fromJSON("data.json") 

Converting JSON to DataFrame using pandas and json libraries in Python

# import packages
import pandas as pd
import numpy as np
import json

# Show numbers inside the dataframe with 2 decimal places
pd.set_option('display.precision', 2)

# Read data
with open(r'Data/CEMACS/11c408d7-6827-11ee-a4c5-3b549db7c439.json', 'r') as f:
    data = json.load(f)

print(f'{"="*10} Cite {"="*10}\n')
display(data["cite"])
print(f'\n{"="*10} Station {"="*10}\n')
display(data["station"])
print(f'\n{"="*10} unit {"="*10}\n')
display(data["unit"])

# Make a dataframe from the json file
df = pd.json_normalize(data['body'])

# Convert dateTime column to date and time type
df['dateTime'] = pd.to_datetime(df['dateTime'])

# Convert all other columns to their appropriate types
for column in df.columns:
    # If column is not dateTime, check its type
    if column != 'dateTime':
        # Try to convert the column to numeric (float)
        try:
            df[column] = df[column].astype(float)
        # If error, then convert the column to string
        except ValueError:
            df[column] = df[column].astype(str)

# Rename the columns: remove long prefixes and use only the last part after the last dot
df.columns = [col.split('.')[-1] for col in df.columns]
df.head().T

Atmosfera USM Data Policy

The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.

The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.

Data users who intend to publish research using data must:

Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.

CC-BY-4.0

CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.

Data use should follow these attribution guidelines for CC-BY-4.0:

• Cite the data-collection paper, for example, cite Yusup et al. 2020.
• List the site by its DOI in the paper (these DOIs are provided with the download).

It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.

Atmosfera USM Data Policy

The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.

The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.

Data users who intend to publish research using data must:

Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.

CC-BY-4.0

CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.

Data use should follow these attribution guidelines for CC-BY-4.0:

• Cite the data-collection paper, for example, cite Yusup et al. 2020.
• List the site by its DOI in the paper (these DOIs are provided with the download).

It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.

How to use the data

Converting JSON to DataFrame using jsonlite package in R

# Load the library; ensure that you have installed it first
# install.packages('jsonlite', dependencies=TRUE, repos='http://cran.rstudio.com/')
library(jsonlite)

# Give the input file name to the function. Place the JSON file in the working directory
data <- fromJSON("data.json") 

Converting JSON to DataFrame using pandas and json libraries in Python

# import packages
import pandas as pd
import numpy as np
import json

# Show numbers inside the dataframe with 2 decimal places
pd.set_option('display.precision', 2)

# Read data
with open(r'Data/CEMACS/11c408d7-6827-11ee-a4c5-3b549db7c439.json', 'r') as f:
    data = json.load(f)

print(f'{"="*10} Cite {"="*10}\n')
display(data["cite"])
print(f'\n{"="*10} Station {"="*10}\n')
display(data["station"])
print(f'\n{"="*10} unit {"="*10}\n')
display(data["unit"])

# Make a dataframe from the json file
df = pd.json_normalize(data['body'])

# Convert dateTime column to date and time type
df['dateTime'] = pd.to_datetime(df['dateTime'])

# Convert all other columns to their appropriate types
for column in df.columns:
    # If column is not dateTime, check its type
    if column != 'dateTime':
        # Try to convert the column to numeric (float)
        try:
            df[column] = df[column].astype(float)
        # If error, then convert the column to string
        except ValueError:
            df[column] = df[column].astype(str)

# Rename the columns: remove long prefixes and use only the last part after the last dot
df.columns = [col.split('.')[-1] for col in df.columns]
df.head().T