Requesting Statistics from the USGS Statistics Service

The USGS calculates various types of statistics for its data and provides these values through a web service. You can access this service through the stats function. Learn more about the USGS Statistics Service.

There are three types of report that you can request using the StatReportType parameter.

  • ‘annual’: This summarizes all of the official daily data for each year using max, min, mean, and the 5, 10, 20, 25, 50, 75, 80, 90, and 95th percentiles.
  • ‘monthly’: This calculates the mean of the 28 to 31 daily values that occur for each of the months in each of the years of record.
  • ‘daily’: This summarizes all of the data for this month and day, using max, min, mean, and the 5, 10, 20, 25, 50, 75, 80, 90, and 95th percentiles.

Request multiple sites

You can request multiple sites by separating them with commas, like this: '01541200,01542500'

Providing additional arguments

The USGS Statistics Service allows you to specify a wide array of additional parameters in your request. You can provide these parameters as keyword arguments, like in this example:

hf.stats('01452500', parameterCD='00060')

This will only request statistics for discharge, which is specified with the ‘00060’ parameter code.

Limiting requests to only certain parameters

The default behavior for the USGS Statistics Service is to provide statistics for every parameter that is collected at a site. This can make for a long table that you will have to filter by the parameter that you want, like this:

my_stat_dataframe.loc(my_stat_dataframe['parameter_cd']='00060')

Alternatively, you can just request the parameter that you are interested in, rather than all of the parameters. To limit your request, provide the parameterCD keyword argument, like this:

hf.stats('01452500', parameterCD='00060')

You can request more than one parameter by listing every parameter code that you are interested in, separated by a comma: parameterCD='00060,00065'

Calculating annual statistics using water years

The default behavior for the USGS Statistics Service is to calculate annual statistics using calendar years. Unfortunately, for many places in the US, this will split the wet season in half. Since discharge data tends to be autocorrelated, you are more likely to get a large flood in January 2020 if you had a large flood in December 2019. To fix this, hydrologists often use ‘Water Years’, which split the year during the more or less dry season, on October 1st. To calculate annual statistics using the water year, provide the statYearType='water' argument, like this:

hf.stats('01452500','annual', statYearType='water')

Missing data

The default behavior for the USGS Statistics Service is to not calculate statistics for months or years if there are -ANY- missing values. In other words, in an annual report, every year reported will be based on 365 or 366 (leap year) values. You can override this behavior by providing the missingData='on' parameter. This will calculate the statistics as long as there are at least one measurement. You can decide whether or not to use the statistic by looking at the count_nu column to see how many values were used to generate the statistic.

Viewing the metadata header or the data

The USGS accompanies every dataset with a header that explains the data. Hydrofunctions will automatically display this header along with the data. To access just one item, use either the .header or .df attribute.

test = stats('01542500')

test        # Print the header & dataframe
test.header # print just the header
test.df     # print just the dataframe.

Examples

The first step as always is to import hydrofunctions.

[1]:
import hydrofunctions as hf
print(hf.__version__)
0.2.0

To get started, let’s request some data from Karthus, PA to see what typically gets collected there.

[2]:
may_2019 = hf.NWIS('01542500', 'dv', '2019-05-01', '2019-06-01')
may_2019
Requested data from https://waterservices.usgs.gov/nwis/dv/?format=json%2C1.1&sites=01542500&startDT=2019-05-01&endDT=2019-06-01
[2]:
USGS:01542500: WB Susquehanna River at Karthaus, PA
    00010: <Day>  Temperature, water, degrees Celsius
    00060: <Day>  Discharge, cubic feet per second
    00095: <Day>  Specific conductance, water, unfiltered, microsiemens per centimeter at 25 degrees Celsius
    00300: <Day>  Dissolved oxygen, water, unfiltered, milligrams per liter
    00400: <Day>  pH, water, unfiltered, field, standard units
Start: 2019-05-01 00:00:00+00:00
End:   2019-06-01 00:00:00+00:00

Requesting annual statistics

This site has collected discharge data since 1960, but other parameters, such as water temperature (‘00010’), have only been collected since 2010. Unfortunately, in 2010, only 41 days of water temperature measurements were collected. By setting the missingData argument to on, we can ask the USGS to report averages for incomplete years. Now it is up to you to decide if 41 values is an adequate number!

[3]:
annual_stats = hf.stats('01542500', 'annual', missingData='on')
# Use annual_stats.header to access just the header, or .df for just the dataframe.
# If you don't specify, both will be provided.
annual_stats
Retrieving annual statistics for site #01542500 from https://waterservices.usgs.gov/nwis/stat/?statReportType=annual&statType=all&sites=01542500&format=rdb&missingData=on
[3]:

#
#
# US Geological Survey, Water Resources Data
# retrieved: 2020-03-04 21:24:34 -05:00 (natwebcaas01)
#
# This file contains USGS Annual Statistics
#
# Note:The statistics generated are based on approved daily-mean data and may not match those published by the USGS in official publications.
# The user is responsible for assessment and use of statistics from this site.
# For more details on why the statistics may not match, visit http://help.waterdata.usgs.gov/faq/about-statistics.
#
# Data heading explanations.
# agency_cd -- agency code
# site_no -- Site identification number
# parameter_cd -- Parameter code
# station_nm -- Site name
# loc_web_ds -- Additional measurement description
#
# Data for the following 1 site(s) are contained in this file
# agency_cd site_no parameter_cd station_nm (loc_web_ds)
# USGS 01542500 00010 WB Susquehanna River at Karthaus, PA
# USGS 01542500 00060 WB Susquehanna River at Karthaus, PA
# USGS 01542500 00095 WB Susquehanna River at Karthaus, PA
# USGS 01542500 00300 WB Susquehanna River at Karthaus, PA
#
# Explanation of Parameter Codes
# parameter_cd Parameter Name
# 00010 Temperature, water, degrees Celsius
# 00060 Discharge, cubic feet per second
# 00095 Specific conductance, water, unfiltered, microsiemens per centimeter at 25 degrees Celsius
# 00300 Dissolved oxygen, water, unfiltered, milligrams per liter
#
# Data heading explanations.
# year_nu ... Calendar year for value.
# mean_va ... Mean of daily mean values for this month.
# count_nu ... Number of values used in the calculation.
#

agency_cd site_no parameter_cd ts_id loc_web_ds year_nu mean_va count_nu
0 USGS 01542500 00010 118870 NaN 2010 4.70 41
1 USGS 01542500 00010 118870 NaN 2011 12.92 354
2 USGS 01542500 00010 118870 NaN 2012 13.98 360
3 USGS 01542500 00010 118870 NaN 2013 12.76 365
4 USGS 01542500 00010 118870 NaN 2014 12.43 362
5 USGS 01542500 00010 118870 NaN 2015 12.46 365
6 USGS 01542500 00010 118870 NaN 2016 12.64 358
7 USGS 01542500 00010 118870 NaN 2017 12.37 358
8 USGS 01542500 00010 118870 NaN 2018 11.64 353
9 USGS 01542500 00010 118870 NaN 2019 11.80 362
10 USGS 01542500 00010 118870 NaN 2020 2.46 14
11 USGS 01542500 00060 118867 NaN 1960 325.50 92
12 USGS 01542500 00060 118867 NaN 1961 2418.00 365
13 USGS 01542500 00060 118867 NaN 1962 2048.00 365
14 USGS 01542500 00060 118867 NaN 1963 1682.00 365
15 USGS 01542500 00060 118867 NaN 1964 2247.00 366
16 USGS 01542500 00060 118867 NaN 1965 1820.00 365
17 USGS 01542500 00060 118867 NaN 1966 2019.00 365
18 USGS 01542500 00060 118867 NaN 1967 2693.00 365
19 USGS 01542500 00060 118867 NaN 1968 2045.00 366
20 USGS 01542500 00060 118867 NaN 1969 1624.00 365
21 USGS 01542500 00060 118867 NaN 1970 3063.00 365
22 USGS 01542500 00060 118867 NaN 1971 2522.00 365
23 USGS 01542500 00060 118867 NaN 1972 3923.00 366
24 USGS 01542500 00060 118867 NaN 1973 2796.00 365
25 USGS 01542500 00060 118867 NaN 1974 2713.00 365
26 USGS 01542500 00060 118867 NaN 1975 3232.00 365
27 USGS 01542500 00060 118867 NaN 1976 2319.00 366
28 USGS 01542500 00060 118867 NaN 1977 3114.00 365
29 USGS 01542500 00060 118867 NaN 1978 2670.00 365
... ... ... ... ... ... ... ... ...
50 USGS 01542500 00060 118867 NaN 2010 2222.00 365
51 USGS 01542500 00060 118867 NaN 2011 3398.00 365
52 USGS 01542500 00060 118867 NaN 2012 1793.00 366
53 USGS 01542500 00060 118867 NaN 2013 1845.00 365
54 USGS 01542500 00060 118867 NaN 2014 2017.00 365
55 USGS 01542500 00060 118867 NaN 2015 2462.00 365
56 USGS 01542500 00060 118867 NaN 2016 1860.00 366
57 USGS 01542500 00060 118867 NaN 2017 2494.00 365
58 USGS 01542500 00060 118867 NaN 2018 4482.00 365
59 USGS 01542500 00060 118867 NaN 2019 2781.00 346
60 USGS 01542500 00095 118873 NaN 2010 363.40 41
61 USGS 01542500 00095 118873 NaN 2011 391.70 354
62 USGS 01542500 00095 118873 NaN 2012 413.90 358
63 USGS 01542500 00095 118873 NaN 2013 401.70 365
64 USGS 01542500 00095 118873 NaN 2014 376.40 362
65 USGS 01542500 00095 118873 NaN 2015 387.10 365
66 USGS 01542500 00095 118873 NaN 2016 404.50 358
67 USGS 01542500 00095 118873 NaN 2017 385.20 358
68 USGS 01542500 00095 118873 NaN 2018 296.70 353
69 USGS 01542500 00095 118873 NaN 2019 346.40 362
70 USGS 01542500 00095 118873 NaN 2020 260.60 14
71 USGS 01542500 00300 118879 NaN 2011 9.56 227
72 USGS 01542500 00300 118879 NaN 2012 9.42 243
73 USGS 01542500 00300 118879 NaN 2013 9.38 246
74 USGS 01542500 00300 118879 NaN 2014 9.45 224
75 USGS 01542500 00300 118879 NaN 2015 9.91 258
76 USGS 01542500 00300 118879 NaN 2016 9.30 208
77 USGS 01542500 00300 118879 NaN 2017 9.07 205
78 USGS 01542500 00300 118879 NaN 2018 9.71 227
79 USGS 01542500 00300 118879 NaN 2019 9.33 164

80 rows × 8 columns

Requesting monthly statistics

The monthly report provides the mean value for each parameter for every month since 1960, when data collection began at this site.

Since this site collects lots of parameters, we can limit our display of the dataframe by filtering everything out except the discharge parameter (‘00060’).

[4]:
monthly_stats = hf.stats('01542500', 'monthly')
monthly_stats.df.loc[monthly_stats.df['parameter_cd']=='00060']
Retrieving monthly statistics for site #01542500 from https://waterservices.usgs.gov/nwis/stat/?statReportType=monthly&statType=all&sites=01542500&format=rdb
[4]:
agency_cd site_no parameter_cd ts_id loc_web_ds year_nu month_nu mean_va count_nu
93 USGS 01542500 00060 118867 NaN 1960 10 258.8 31
94 USGS 01542500 00060 118867 NaN 1960 11 441.1 30
95 USGS 01542500 00060 118867 NaN 1960 12 280.5 31
96 USGS 01542500 00060 118867 NaN 1961 1 474.2 31
97 USGS 01542500 00060 118867 NaN 1961 2 5155.0 28
98 USGS 01542500 00060 118867 NaN 1961 3 6108.0 31
99 USGS 01542500 00060 118867 NaN 1961 4 6145.0 30
100 USGS 01542500 00060 118867 NaN 1961 5 3320.0 31
101 USGS 01542500 00060 118867 NaN 1961 6 2109.0 30
102 USGS 01542500 00060 118867 NaN 1961 7 1004.0 31
103 USGS 01542500 00060 118867 NaN 1961 8 1107.0 31
104 USGS 01542500 00060 118867 NaN 1961 9 564.7 30
105 USGS 01542500 00060 118867 NaN 1961 10 286.6 31
106 USGS 01542500 00060 118867 NaN 1961 11 1576.0 30
107 USGS 01542500 00060 118867 NaN 1961 12 1457.0 31
108 USGS 01542500 00060 118867 NaN 1962 1 2391.0 31
109 USGS 01542500 00060 118867 NaN 1962 2 2387.0 28
110 USGS 01542500 00060 118867 NaN 1962 3 6124.0 31
111 USGS 01542500 00060 118867 NaN 1962 4 7340.0 30
112 USGS 01542500 00060 118867 NaN 1962 5 1699.0 31
113 USGS 01542500 00060 118867 NaN 1962 6 707.5 30
114 USGS 01542500 00060 118867 NaN 1962 7 296.1 31
115 USGS 01542500 00060 118867 NaN 1962 8 271.0 31
116 USGS 01542500 00060 118867 NaN 1962 9 586.3 30
117 USGS 01542500 00060 118867 NaN 1962 10 891.4 31
118 USGS 01542500 00060 118867 NaN 1962 11 1267.0 30
119 USGS 01542500 00060 118867 NaN 1962 12 704.3 31
120 USGS 01542500 00060 118867 NaN 1963 1 1666.0 31
121 USGS 01542500 00060 118867 NaN 1963 2 706.1 28
122 USGS 01542500 00060 118867 NaN 1963 3 7965.0 31
... ... ... ... ... ... ... ... ... ...
616 USGS 01542500 00060 118867 NaN 2017 6 3073.0 30
617 USGS 01542500 00060 118867 NaN 2017 7 1582.0 31
618 USGS 01542500 00060 118867 NaN 2017 8 810.5 31
619 USGS 01542500 00060 118867 NaN 2017 9 450.4 30
620 USGS 01542500 00060 118867 NaN 2017 10 724.0 31
621 USGS 01542500 00060 118867 NaN 2017 11 2341.0 30
622 USGS 01542500 00060 118867 NaN 2017 12 1265.0 31
623 USGS 01542500 00060 118867 NaN 2018 1 2708.0 31
624 USGS 01542500 00060 118867 NaN 2018 2 7874.0 28
625 USGS 01542500 00060 118867 NaN 2018 3 3952.0 31
626 USGS 01542500 00060 118867 NaN 2018 4 4711.0 30
627 USGS 01542500 00060 118867 NaN 2018 5 4117.0 31
628 USGS 01542500 00060 118867 NaN 2018 6 3448.0 30
629 USGS 01542500 00060 118867 NaN 2018 7 2900.0 31
630 USGS 01542500 00060 118867 NaN 2018 8 2458.0 31
631 USGS 01542500 00060 118867 NaN 2018 9 7562.0 30
632 USGS 01542500 00060 118867 NaN 2018 10 4185.0 31
633 USGS 01542500 00060 118867 NaN 2018 11 5450.0 30
634 USGS 01542500 00060 118867 NaN 2018 12 4855.0 31
635 USGS 01542500 00060 118867 NaN 2019 1 3982.0 31
636 USGS 01542500 00060 118867 NaN 2019 2 5452.0 28
637 USGS 01542500 00060 118867 NaN 2019 3 3927.0 31
638 USGS 01542500 00060 118867 NaN 2019 4 4020.0 30
639 USGS 01542500 00060 118867 NaN 2019 5 4316.0 31
640 USGS 01542500 00060 118867 NaN 2019 6 3618.0 30
641 USGS 01542500 00060 118867 NaN 2019 7 1594.0 31
642 USGS 01542500 00060 118867 NaN 2019 8 855.8 31
643 USGS 01542500 00060 118867 NaN 2019 9 810.0 30
644 USGS 01542500 00060 118867 NaN 2019 10 795.1 31
645 USGS 01542500 00060 118867 NaN 2019 11 1357.0 30

553 rows × 9 columns

Requesting daily reports

The daily statistics report is different from the monthly and annual reports in that it aggregates multiple years together from across the entire period of record. So in the following example, in line 0, the report provides statistics for January 1st by calculating the mean of every January 1st from 1961 (‘begin_yr’) to 2019 (‘end_yr’).

Note that there are 366 rows, or 365 days each year plus Febrary 29th on leap years.

[5]:
daily_stats = hf.stats('01542500', 'daily', parameterCd='00060')
daily_stats.df
Retrieving daily statistics for site #01542500 from https://waterservices.usgs.gov/nwis/stat/?statReportType=daily&statType=all&sites=01542500&format=rdb&parameterCd=00060
[5]:
agency_cd site_no parameter_cd ts_id loc_web_ds month_nu day_nu begin_yr end_yr count_nu ... mean_va p05_va p10_va p20_va p25_va p50_va p75_va p80_va p90_va p95_va
0 USGS 01542500 00060 118867 NaN 1 1 1961 2019 46 ... 2850 520.0 807 970 1080 2180 3790 4340 6800 7600.0
1 USGS 01542500 00060 118867 NaN 1 2 1961 2019 46 ... 2950 487.0 800 1040 1100 2080 3730 3960 6400 9460.0
2 USGS 01542500 00060 118867 NaN 1 3 1961 2019 46 ... 2880 523.0 793 1110 1290 2110 3400 4590 6450 8390.0
3 USGS 01542500 00060 118867 NaN 1 4 1961 2019 46 ... 2720 541.0 753 1120 1280 1890 3280 4190 6070 7510.0
4 USGS 01542500 00060 118867 NaN 1 5 1961 2019 46 ... 2710 551.0 716 1080 1180 1850 3880 4480 5760 8090.0
5 USGS 01542500 00060 118867 NaN 1 6 1961 2019 46 ... 2850 556.0 802 1040 1120 2140 3820 4420 6160 7460.0
6 USGS 01542500 00060 118867 NaN 1 7 1961 2019 46 ... 2780 576.0 819 1020 1100 1900 3650 4060 5500 6930.0
7 USGS 01542500 00060 118867 NaN 1 8 1961 2019 46 ... 2630 603.0 792 976 1100 1770 3700 4050 4870 6090.0
8 USGS 01542500 00060 118867 NaN 1 9 1961 2019 46 ... 2710 621.0 788 929 1130 1920 3620 3720 5280 8450.0
9 USGS 01542500 00060 118867 NaN 1 10 1961 2019 46 ... 2560 696.0 847 961 1070 1720 3320 3700 5370 7960.0
10 USGS 01542500 00060 118867 NaN 1 11 1961 2019 46 ... 2430 738.0 829 979 1100 1660 3340 3780 5170 6370.0
11 USGS 01542500 00060 118867 NaN 1 12 1961 2019 46 ... 2450 649.0 773 1070 1240 1750 3150 3480 4620 6550.0
12 USGS 01542500 00060 118867 NaN 1 13 1961 2019 46 ... 2750 621.0 771 1000 1170 2020 3690 4130 6160 7620.0
13 USGS 01542500 00060 118867 NaN 1 14 1961 2019 46 ... 2760 607.0 778 1000 1190 1900 3780 3940 6600 7040.0
14 USGS 01542500 00060 118867 NaN 1 15 1961 2019 46 ... 2640 614.0 740 974 1080 1900 3520 4050 5850 7560.0
15 USGS 01542500 00060 118867 NaN 1 16 1961 2019 46 ... 2480 601.0 724 938 1040 1790 3250 3340 4630 7750.0
16 USGS 01542500 00060 118867 NaN 1 17 1961 2019 46 ... 2420 587.0 716 860 948 2040 2910 3440 5160 6920.0
17 USGS 01542500 00060 118867 NaN 1 18 1961 2019 46 ... 2380 554.0 715 893 988 1780 2950 3630 6000 7630.0
18 USGS 01542500 00060 118867 NaN 1 19 1961 2019 46 ... 2390 564.0 687 964 1120 1610 2760 3540 5490 7260.0
19 USGS 01542500 00060 118867 NaN 1 20 1961 2019 46 ... 2340 570.0 678 962 1090 1740 3160 3470 4700 6780.0
20 USGS 01542500 00060 118867 NaN 1 21 1961 2019 46 ... 2340 544.0 655 894 1070 1690 2960 3270 5060 6480.0
21 USGS 01542500 00060 118867 NaN 1 22 1961 2019 46 ... 2330 581.0 662 952 1100 1470 2830 3080 4750 7770.0
22 USGS 01542500 00060 118867 NaN 1 23 1961 2019 46 ... 2250 572.0 662 991 1070 1640 2870 3260 3980 6860.0
23 USGS 01542500 00060 118867 NaN 1 24 1961 2019 46 ... 2340 544.0 667 1000 1000 1510 3150 3550 4870 5960.0
24 USGS 01542500 00060 118867 NaN 1 25 1961 2019 46 ... 2780 521.0 716 989 1040 1620 3860 4550 6270 8750.0
25 USGS 01542500 00060 118867 NaN 1 26 1961 2019 46 ... 2950 492.0 772 993 1100 1740 3830 4130 6700 8240.0
26 USGS 01542500 00060 118867 NaN 1 27 1961 2019 46 ... 3040 496.0 757 1070 1090 1860 3900 5470 7430 7980.0
27 USGS 01542500 00060 118867 NaN 1 28 1961 2019 46 ... 2960 510.0 766 999 1050 2050 4180 4730 6530 9460.0
28 USGS 01542500 00060 118867 NaN 1 29 1961 2019 46 ... 2750 497.0 791 928 956 2210 3880 4370 5970 8140.0
29 USGS 01542500 00060 118867 NaN 1 30 1961 2019 46 ... 2880 487.0 800 888 943 1930 3780 4430 6130 7100.0
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
336 USGS 01542500 00060 118867 NaN 12 2 1961 2020 47 ... 3010 375.0 784 1130 1180 1880 3710 4400 6840 9630.0
337 USGS 01542500 00060 118867 NaN 12 3 1961 2020 47 ... 2810 415.0 782 1090 1170 2030 3750 4040 6500 7330.0
338 USGS 01542500 00060 118867 NaN 12 4 1961 2020 47 ... 2720 401.0 745 994 1070 1930 3720 4370 5820 6970.0
339 USGS 01542500 00060 118867 NaN 12 5 1961 2020 47 ... 2670 517.0 757 967 1070 1830 3850 4020 5980 6920.0
340 USGS 01542500 00060 118867 NaN 12 6 1961 2020 47 ... 2650 708.0 871 994 1310 1800 3570 4180 5590 7450.0
341 USGS 01542500 00060 118867 NaN 12 7 1961 2020 47 ... 2810 713.0 812 1070 1270 2140 3770 4210 5330 7230.0
342 USGS 01542500 00060 118867 NaN 12 8 1961 2020 47 ... 2790 535.0 730 1050 1310 2220 3900 4150 4650 9390.0
343 USGS 01542500 00060 118867 NaN 12 9 1961 2020 47 ... 2800 483.0 690 1130 1370 2140 3480 3890 5640 9520.0
344 USGS 01542500 00060 118867 NaN 12 10 1961 2020 47 ... 2850 407.0 718 1120 1320 2170 3720 4320 5630 8720.0
345 USGS 01542500 00060 118867 NaN 12 11 1961 2020 47 ... 2980 444.0 673 1320 1650 2440 3680 4130 6360 8870.0
346 USGS 01542500 00060 118867 NaN 12 12 1961 2020 47 ... 2890 624.0 935 1330 1400 2430 4000 4360 6440 7060.0
347 USGS 01542500 00060 118867 NaN 12 13 1961 2019 46 ... 2880 637.0 906 1190 1380 2440 4350 4580 5490 6460.0
348 USGS 01542500 00060 118867 NaN 12 14 1961 2019 46 ... 2750 695.0 893 1200 1340 2430 3750 4240 4880 7310.0
349 USGS 01542500 00060 118867 NaN 12 15 1961 2019 46 ... 2670 684.0 770 1100 1270 2120 3760 4100 5020 7450.0
350 USGS 01542500 00060 118867 NaN 12 16 1961 2019 46 ... 2610 531.0 766 1030 1270 2110 3710 3950 4830 6140.0
351 USGS 01542500 00060 118867 NaN 12 17 1961 2019 46 ... 2600 530.0 707 1020 1190 2230 3510 4100 4740 6160.0
352 USGS 01542500 00060 118867 NaN 12 18 1961 2019 46 ... 2510 580.0 669 1030 1180 2250 3630 3870 4540 5150.0
353 USGS 01542500 00060 118867 NaN 12 19 1961 2019 46 ... 2670 611.0 660 1020 1210 2120 3260 3440 4390 10400.0
354 USGS 01542500 00060 118867 NaN 12 20 1961 2019 46 ... 2680 576.0 662 1050 1200 2000 3160 3510 5740 10000.0
355 USGS 01542500 00060 118867 NaN 12 21 1961 2019 46 ... 2690 535.0 683 1000 1200 1900 3820 4480 5980 8600.0
356 USGS 01542500 00060 118867 NaN 12 22 1961 2019 46 ... 3020 587.0 682 959 1230 1890 5000 5810 7070 8830.0
357 USGS 01542500 00060 118867 NaN 12 23 1961 2019 46 ... 2990 607.0 718 1110 1450 1920 4160 4540 7530 8910.0
358 USGS 01542500 00060 118867 NaN 12 24 1961 2019 46 ... 3060 607.0 660 1250 1310 1950 3830 4820 7250 8070.0
359 USGS 01542500 00060 118867 NaN 12 25 1961 2019 46 ... 3160 601.0 718 1140 1340 2530 4370 4800 6590 8800.0
360 USGS 01542500 00060 118867 NaN 12 26 1961 2019 46 ... 3040 544.0 770 1130 1380 2660 4280 4730 5840 8060.0
361 USGS 01542500 00060 118867 NaN 12 27 1961 2019 46 ... 3030 499.0 720 1040 1280 2600 4100 4610 5810 8770.0
362 USGS 01542500 00060 118867 NaN 12 28 1961 2019 46 ... 3060 525.0 658 1050 1200 2530 4500 4570 5800 8950.0
363 USGS 01542500 00060 118867 NaN 12 29 1961 2019 46 ... 2980 528.0 727 1030 1100 2560 4130 4480 6180 7660.0
364 USGS 01542500 00060 118867 NaN 12 30 1961 2019 46 ... 2830 514.0 680 961 1080 2440 3820 4390 6130 7520.0
365 USGS 01542500 00060 118867 NaN 12 31 1961 2019 46 ... 2890 533.0 706 924 1110 2270 4130 4550 6050 7770.0

366 rows × 24 columns