Export 100 rows to a notebook

Back to the rows

You can export this data to a Jupyter or Observable notebook by copying and pasting the following:

Jupyter

Make sure you have Pandas. Import it in a cell like this:

import pandas
If this shows an error you can run %pip install pandas in a notebook cell to install it.

Now paste the following into a cell to load the 100 rows into a DataFrame called df:

df = pandas.read_json(
    "http://ejscreen-merged.envirodatagov.org/ejscreen_merged/ejscreen_single_table.json?_shape=array"
)

Run df in a new cell to see the table.

You can export all rows using a single streaming CSV export like this:

df = pandas.read_csv(
    "http://ejscreen-merged.envirodatagov.org/ejscreen_merged/ejscreen_single_table.csv?_stream=on", dtype={
    "rowid": int,
    "ID": int,
    "REGION": int,
    "ACSTOTPOP": float,
    "ACSIPOVBAS": float,
    "ACSEDUCBAS": float,
    "ACSTOTHH": float,
    "ACSTOTHU": float,
    "ACSUNEMPBAS": float,
    "ACSDISABBAS": float,
    "DEMOGIDX_2": float,
    "DEMOGIDX_5": float,
    "PEOPCOLOR": float,
    "PEOPCOLORPCT": float,
    "LOWINCOME": float,
    "LOWINCPCT": float,
    "UNEMPLOYED": float,
    "UNEMPPCT": float,
    "DISABILITY": float,
    "DISABILITYPCT": float,
    "LINGISO": float,
    "LINGISOPCT": float,
    "LESSHS": float,
    "LESSHSPCT": float,
    "UNDER5": float,
    "UNDER5PCT": float,
    "OVER64": float,
    "OVER64PCT": float,
    "PM25": float,
    "OZONE": float,
    "DSLPM": float,
    "RSEI_AIR": float,
    "PTRAF": float,
    "PRE1960": float,
    "PRE1960PCT": float,
    "PNPL": float,
    "PRMP": float,
    "PTSDF": float,
    "UST": float,
    "PWDIS": float,
    "NO2": float,
    "DWATER": float,
    "D2_PM25": float,
    "D5_PM25": float,
    "D2_OZONE": float,
    "D5_OZONE": float,
    "D2_DSLPM": float,
    "D5_DSLPM": float,
    "D2_RSEI_AIR": float,
    "D5_RSEI_AIR": float,
    "D2_PTRAF": float,
    "D5_PTRAF": float,
    "D2_LDPNT": float,
    "D5_LDPNT": float,
    "D2_PNPL": float,
    "D5_PNPL": float,
    "D2_PRMP": float,
    "D5_PRMP": float,
    "D2_PTSDF": float,
    "D5_PTSDF": float,
    "D2_UST": float,
    "D5_UST": float,
    "D2_PWDIS": float,
    "D5_PWDIS": float,
    "D2_NO2": float,
    "D5_NO2": float,
    "D2_DWATER": float,
    "D5_DWATER": float,
    "P_DEMOGIDX_2": float,
    "P_DEMOGIDX_5": float,
    "P_PEOPCOLORPCT": float,
    "P_LOWINCPCT": float,
    "P_UNEMPPCT": float,
    "P_DISABILITYPCT": float,
    "P_LINGISOPCT": float,
    "P_LESSHSPCT": float,
    "P_UNDER5PCT": float,
    "P_OVER64PCT": float,
    "P_PM25": float,
    "P_OZONE": float,
    "P_DSLPM": float,
    "P_RSEI_AIR": float,
    "P_PTRAF": float,
    "P_LDPNT": float,
    "P_PNPL": float,
    "P_PRMP": float,
    "P_PTSDF": float,
    "P_UST": float,
    "P_PWDIS": float,
    "P_NO2": float,
    "P_DWATER": float,
    "P_D2_PM25": float,
    "P_D5_PM25": float,
    "P_D2_OZONE": float,
    "P_D5_OZONE": float,
    "P_D2_DSLPM": float,
    "P_D5_DSLPM": float,
    "P_D2_RSEI_AIR": float,
    "P_D5_RSEI_AIR": float,
    "P_D2_PTRAF": float,
    "P_D5_PTRAF": float,
    "P_D2_LDPNT": float,
    "P_D5_LDPNT": float,
    "P_D2_PNPL": float,
    "P_D5_PNPL": float,
    "P_D2_PRMP": float,
    "P_D5_PRMP": float,
    "P_D2_PTSDF": float,
    "P_D5_PTSDF": float,
    "P_D2_UST": float,
    "P_D5_UST": float,
    "P_D2_PWDIS": float,
    "P_D5_PWDIS": float,
    "P_D2_NO2": float,
    "P_D5_NO2": float,
    "P_D2_DWATER": float,
    "P_D5_DWATER": float,
    "AREALAND": float,
    "AREAWATER": float,
    "NPL_CNT": float,
    "TSDF_CNT": float,
    "EXCEED_COUNT_80": float,
    "EXCEED_COUNT_80_SUP": float,
    "DEMOGIDX_2ST": float,
    "DEMOGIDX_5ST": float,
    "Shape_Length": float,
    "Shape_Area": float,
    "percentile_wildfire": float,
    "percentile_flood": float,
    "Days_Above_90_2019": float,
    "Days_Above_90_2020": float,
    "Days_Above_90_2021": float,
    "Days_Above_90_2022": float,
    "Days_Above_90_2023": float,
    "Max_Days_Above_90": float,
    "Average_Days_Above_90": float,
    "bgfips": int,
    "RAW_CG_NOHINCPCT": float,
    "S_CG_NOHINCPCT_AVG": float,
    "S_CG_NOHINCPCT_PCTILE": float,
    "N_CG_NOHINCPCT_AVG": float,
    "N_CG_NOHINCPCT_PCTILE": float,
    "RAW_HI_HEARTDISEASE": float,
    "S_HI_HEARTDISEASE_AVG": float,
    "S_HI_HEARTDISEASE_PCTILE": float,
    "N_HI_HEARTDISEASE_AVG": float,
    "N_HI_HEARTDISEASE_PCTILE": float,
    "RAW_HI_ASTHMA": float,
    "S_HI_ASTHMA_AVG": float,
    "S_HI_ASTHMA_PCTILE": float,
    "N_HI_ASTHMA_AVG": float,
    "N_HI_ASTHMA_PCTILE": float,
    "RAW_HI_CANCER": float,
    "S_HI_CANCER_AVG": float,
    "S_HI_CANCER_PCTILE": float,
    "N_HI_CANCER_AVG": float,
    "N_HI_CANCER_PCTILE": float,
    "RAW_CI_FLOOD30": float,
    "S_CI_FLOOD30_AVG": float,
    "S_CI_FLOOD30_PCTILE": float,
    "N_CI_FLOOD30_AVG": float,
    "N_CI_FLOOD30_PCTILE": float,
    "RAW_CI_FIRE30": float,
    "S_CI_FIRE30_AVG": float,
    "S_CI_FIRE30_PCTILE": float,
    "N_CI_FIRE30_AVG": float,
    "N_CI_FIRE30_PCTILE": float,
    "NUM_NPL": float,
    "NUM_TSDF": float,
    "NUM_WATERDIS": float,
    "NUM_AIRPOLL": float,
    "NUM_BROWNFIELD": float,
    "NUM_TRI": float,
    "NUM_SCHOOL": float,
    "NUM_HOSPITAL": float,
    "NUM_CHURCH": float,
    "P_ENGLISH": float,
    "P_SPANISH": float,
    "P_FRENCH": float,
    "P_RUS_POL_SLAV": float,
    "P_OTHER_IE": float,
    "P_VIETNAMESE": float,
    "P_OTHER_ASIAN": float,
    "P_ARABIC": float,
    "P_OTHER": float,
    "P_NON_ENGLISH": float,
    "RAW_CG_LIMITEDBBPCT": float,
    "S_CG_LIMITEDBBPCT_AVG": float,
    "S_CG_LIMITEDBBPCT_PCTILE": float,
    "N_CG_LIMITEDBBPCT_AVG": float,
    "N_CG_LIMITEDBBPCT_PCTILE": float,
})

Observable

Import the data into a variable called rows like this:

rows = d3.json(
  "http://ejscreen-merged.envirodatagov.org/ejscreen_merged/ejscreen_single_table.json?_shape=array"
)

You can export all rows using a single streaming CSV export like this:

rows = d3.csv(
  "http://ejscreen-merged.envirodatagov.org/ejscreen_merged/ejscreen_single_table.csv?_stream=on",
  d3.autoType
)