Exploration of U.S Births from 1994-2003¶

This dataset is from the story Some People Are Too Superstitious To Have A Baby On Friday The 13th.

There are two files:

US_births_1994-2003_CDC_NCHS.csv contains U.S. births data for the years 1994 to 2003, as provided by the Centers for Disease Control and Prevention's National Center for Health Statistics.

US_births_2000-2014_SSA.csv contains U.S. births data for the years 2000 to 2014, as provided by the Social Security Administration.

Both files have the following structure:

Header Definition
year Year
month Month
date_of_month Day number of the month
day_of_week Day of week, where 1 is Monday and 7 is Sunday
births Number of births

We will try to explore the dataset and find some insights. First, we will read the csv file in classical style.

In [31]:
f=open("US_births_1994-2003_CDC_NCHS.csv","r")
text=f.read()
split_text=text.split("\n")
print(split_text[0:11])

['year,month,date_of_month,day_of_week,births', '1994,1,1,6,8096', '1994,1,2,7,7772', '1994,1,3,1,10142', '1994,1,4,2,11248', '1994,1,5,3,11053', '1994,1,6,4,11406', '1994,1,7,5,11251', '1994,1,8,6,8653', '1994,1,9,7,7910', '1994,1,10,1,10498']

We can use object oriented style of reading the csv file by defining a function.

In [32]:
def read_csv(file_name):
    ftext = open(file_name,"r").read()
    string_list = ftext.split("\n")
    string_list = string_list[1:len(string_list)]
    final_list=[]
    for row in string_list:
        int_fields=[]
        string_fields = row.split(",")
        for each in string_fields:
            int_fields.append(int(each))
        final_list.append(int_fields)
    return final_list

cdc_list = read_csv("US_births_1994-2003_CDC_NCHS.csv")
print(cdc_list[0:10])

[[1994, 1, 1, 6, 8096], [1994, 1, 2, 7, 7772], [1994, 1, 3, 1, 10142], [1994, 1, 4, 2, 11248], [1994, 1, 5, 3, 11053], [1994, 1, 6, 4, 11406], [1994, 1, 7, 5, 11251], [1994, 1, 8, 6, 8653], [1994, 1, 9, 7, 7910], [1994, 1, 10, 1, 10498]]
In [33]:
def month_births(input_lst):
    births_per_month={}
    for each in input_lst:
        month = each[1]
        birth = each[4]
        if month in births_per_month:
            births_per_month[month] = births_per_month[month] + birth
        else:
            births_per_month[month] = birth
    return births_per_month



cdc_month_births = month_births(cdc_list)
print(cdc_month_births)

{1: 3232517, 2: 3018140, 3: 3322069, 4: 3185314, 5: 3350907, 6: 3296530, 7: 3498783, 8: 3525858, 9: 3439698, 10: 3378814, 11: 3171647, 12: 3301860}
In [34]:
def dow_births(input_lst):
    birth_per_wday = {}
    for each in input_lst:
        day_of_week = each[3]
        birth = each[4]
        if day_of_week in birth_per_wday:
           birth_per_wday[day_of_week] = birth +  birth_per_wday[day_of_week]
        else:
           birth_per_wday[day_of_week] = birth
        
    return birth_per_wday


cdc_day_births = dow_births(cdc_list)
print(cdc_day_births)            

{1: 5789166, 2: 6446196, 3: 6322855, 4: 6288429, 5: 6233657, 6: 4562111, 7: 4079723}
In [35]:
def calc_counts(data,column):
    births_per_col = {}
    for each in data:
        req_col = each[column]
        birth = each[4]
        if req_col in births_per_col:
            births_per_col[req_col] = birth + births_per_col[req_col]
        else:
            births_per_col[req_col] = birth
    return births_per_col

cdc_year_births = calc_counts(cdc_list,0)

cdc_month_births = calc_counts(cdc_list,1)

cdc_dom_births = calc_counts(cdc_list,2)

cdc_dow_births = calc_counts(cdc_list,3)
In [36]:
cdc_year_births
Out[36]:
{1994: 3952767,
 1995: 3899589,
 1996: 3891494,
 1997: 3880894,
 1998: 3941553,
 1999: 3959417,
 2000: 4058814,
 2001: 4025933,
 2002: 4021726,
 2003: 4089950}
In [37]:
list(cdc_year_births)[0:2]
Out[37]:
[2000, 2001]

Write a function that can calculate the min and max values for any dictionary that's passed in.¶

The function cal_min_max takes 2 arguments :

  • input_dict : the input dictionary
  • input_type : to indicate whether you want min and max as a string value

Returns a single value i.e. min and max as per the specified input_type parameter

In [38]:
def cal_min_max(input_dict, input_type):
    start_index = list(input_dict)[0]
    comp = input_dict[start_index]
    for index in list(input_dict)[1:len(list(input_dict))]:
        if input_type == "min":
            if comp > input_dict[index]:
                comp = input_dict[index]
        if input_type == "max":
            if comp < input_dict[index]:
                comp = input_dict[index]
    return comp

min =cal_min_max(cdc_year_births, "max")
max = cal_min_max(cdc_year_births, "min")

print("The maximum value of dict is",min)
print("The minimum value of dict is",max)

The maximum value of dict is 4089950
The minimum value of dict is 3880894

Write a function that extracts the same values across years and calculates the differences between consecutive values to show if number of births is increasing or decreasing.¶

- For example, how did the number of births on Saturday change each year between 1994 and 2003?

The function cons_diff_year takes 3 arguments :

  • inputlst : Input list
  • inputcol : Column from input list to be considered
  • conscol : Column across which consecutive columns need to be calculated

Returns a dictionary with consecutive difference across years with respective to the consecutive column i.e day of week

In [39]:
def cons_diff_year(inputlst,inputcol,conscol):
    temp_dict = {}
    diff_dict = {}
    for each in inputlst:
        if each[inputcol] == conscol:
            if each[0] in temp_dict:
                temp_dict[each[0]] = each[4] + temp_dict[each[0]]
            else:
                temp_dict[each[0]] = each[4]
        
    for key,value in temp_dict.items():
        if key-1 in temp_dict:
            diff_dict[key] = temp_dict[key] - temp_dict[key-1]
        else:
            diff_dict[key] = 0
 
    return diff_dict


saturday_diff_year = cons_diff_year(cdc_list, 3, 6)

saturday_diff_year
Out[39]:
{1994: 0,
 1995: -15152,
 1996: -3319,
 1997: -5421,
 1998: 2936,
 1999: -3791,
 2000: 19809,
 2001: -15866,
 2002: -8158,
 2003: 1675}

Find a way to combine the CDC data with the SSA data, which you can find here. Specifically, brainstorm ways to deal with the overlapping time periods in the datasets.¶

Approach :

  • First, create a copy of cdc_list and assign it to new comb_list
  • Now, find overlapping time periods between ssa_list and comb_list
    • for every overlapping time period, find average of the values and store it back in comb_list
In [40]:
ssa_list = read_csv("US_births_2000-2014_SSA.csv")

comb_list = cdc_list

for x in comb_list:    
    for  y in ssa_list:
        if (x[0] == y[0]) and (x[1] == y[1]) and (x[2] == y[2])  and (x[3] == y[3]):
            x[4] =  (x[4] + y[4]) / 2

            
comb_list
Out[40]:
[[1994, 1, 1, 6, 8096],
 [1994, 1, 2, 7, 7772],
 [1994, 1, 3, 1, 10142],
 [1994, 1, 4, 2, 11248],
 [1994, 1, 5, 3, 11053],
 [1994, 1, 6, 4, 11406],
 [1994, 1, 7, 5, 11251],
 [1994, 1, 8, 6, 8653],
 [1994, 1, 9, 7, 7910],
 [1994, 1, 10, 1, 10498],
 [1994, 1, 11, 2, 11706],
 [1994, 1, 12, 3, 11567],
 [1994, 1, 13, 4, 11212],
 [1994, 1, 14, 5, 11570],
 [1994, 1, 15, 6, 8660],
 [1994, 1, 16, 7, 8123],
 [1994, 1, 17, 1, 10567],
 [1994, 1, 18, 2, 11541],
 [1994, 1, 19, 3, 11257],
 [1994, 1, 20, 4, 11682],
 [1994, 1, 21, 5, 11811],
 [1994, 1, 22, 6, 8833],
 [1994, 1, 23, 7, 8310],
 [1994, 1, 24, 1, 11125],
 [1994, 1, 25, 2, 11981],
 [1994, 1, 26, 3, 11514],
 [1994, 1, 27, 4, 11702],
 [1994, 1, 28, 5, 11666],
 [1994, 1, 29, 6, 8988],
 [1994, 1, 30, 7, 8096],
 [1994, 1, 31, 1, 10765],
 [1994, 2, 1, 2, 11755],
 [1994, 2, 2, 3, 11483],
 [1994, 2, 3, 4, 11523],
 [1994, 2, 4, 5, 11677],
 [1994, 2, 5, 6, 8991],
 [1994, 2, 6, 7, 8309],
 [1994, 2, 7, 1, 10984],
 [1994, 2, 8, 2, 12152],
 [1994, 2, 9, 3, 11515],
 [1994, 2, 10, 4, 11623],
 [1994, 2, 11, 5, 11517],
 [1994, 2, 12, 6, 8945],
 [1994, 2, 13, 7, 8171],
 [1994, 2, 14, 1, 11551],
 [1994, 2, 15, 2, 12164],
 [1994, 2, 16, 3, 12009],
 [1994, 2, 17, 4, 11674],
 [1994, 2, 18, 5, 11887],
 [1994, 2, 19, 6, 8946],
 [1994, 2, 20, 7, 8402],
 [1994, 2, 21, 1, 10617],
 [1994, 2, 22, 2, 11810],
 [1994, 2, 23, 3, 11776],
 [1994, 2, 24, 4, 11667],
 [1994, 2, 25, 5, 11905],
 [1994, 2, 26, 6, 8988],
 [1994, 2, 27, 7, 8195],
 [1994, 2, 28, 1, 11091],
 [1994, 3, 1, 2, 12127],
 [1994, 3, 2, 3, 11735],
 [1994, 3, 3, 4, 11984],
 [1994, 3, 4, 5, 12066],
 [1994, 3, 5, 6, 9215],
 [1994, 3, 6, 7, 8389],
 [1994, 3, 7, 1, 10996],
 [1994, 3, 8, 2, 12275],
 [1994, 3, 9, 3, 11780],
 [1994, 3, 10, 4, 11792],
 [1994, 3, 11, 5, 11939],
 [1994, 3, 12, 6, 9087],
 [1994, 3, 13, 7, 8248],
 [1994, 3, 14, 1, 11092],
 [1994, 3, 15, 2, 12298],
 [1994, 3, 16, 3, 11865],
 [1994, 3, 17, 4, 11976],
 [1994, 3, 18, 5, 11799],
 [1994, 3, 19, 6, 8944],
 [1994, 3, 20, 7, 8243],
 [1994, 3, 21, 1, 11140],
 [1994, 3, 22, 2, 11964],
 [1994, 3, 23, 3, 11637],
 [1994, 3, 24, 4, 11904],
 [1994, 3, 25, 5, 11568],
 [1994, 3, 26, 6, 8957],
 [1994, 3, 27, 7, 8189],
 [1994, 3, 28, 1, 11051],
 [1994, 3, 29, 2, 12154],
 [1994, 3, 30, 3, 11540],
 [1994, 3, 31, 4, 11782],
 [1994, 4, 1, 5, 10630],
 [1994, 4, 2, 6, 8782],
 [1994, 4, 3, 7, 7530],
 [1994, 4, 4, 1, 10909],
 [1994, 4, 5, 2, 11876],
 [1994, 4, 6, 3, 11811],
 [1994, 4, 7, 4, 11718],
 [1994, 4, 8, 5, 11532],
 [1994, 4, 9, 6, 8791],
 [1994, 4, 10, 7, 8183],
 [1994, 4, 11, 1, 11060],
 [1994, 4, 12, 2, 12146],
 [1994, 4, 13, 3, 11428],
 [1994, 4, 14, 4, 11709],
 [1994, 4, 15, 5, 11753],
 [1994, 4, 16, 6, 8790],
 [1994, 4, 17, 7, 7867],
 [1994, 4, 18, 1, 11094],
 [1994, 4, 19, 2, 11966],
 [1994, 4, 20, 3, 11585],
 [1994, 4, 21, 4, 11509],
 [1994, 4, 22, 5, 11553],
 [1994, 4, 23, 6, 8613],
 [1994, 4, 24, 7, 8089],
 [1994, 4, 25, 1, 10909],
 [1994, 4, 26, 2, 12236],
 [1994, 4, 27, 3, 11701],
 [1994, 4, 28, 4, 11527],
 [1994, 4, 29, 5, 11474],
 [1994, 4, 30, 6, 8621],
 [1994, 5, 1, 7, 8145],
 [1994, 5, 2, 1, 11169],
 [1994, 5, 3, 2, 12023],
 [1994, 5, 4, 3, 11754],
 [1994, 5, 5, 4, 11958],
 [1994, 5, 6, 5, 11904],
 [1994, 5, 7, 6, 8641],
 [1994, 5, 8, 7, 8203],
 [1994, 5, 9, 1, 10914],
 [1994, 5, 10, 2, 11771],
 [1994, 5, 11, 3, 11278],
 [1994, 5, 12, 4, 11822],
 [1994, 5, 13, 5, 11085],
 [1994, 5, 14, 6, 8830],
 [1994, 5, 15, 7, 8253],
 [1994, 5, 16, 1, 11103],
 [1994, 5, 17, 2, 12289],
 [1994, 5, 18, 3, 11668],
 [1994, 5, 19, 4, 11411],
 [1994, 5, 20, 5, 11645],
 [1994, 5, 21, 6, 8830],
 [1994, 5, 22, 7, 8449],
 [1994, 5, 23, 1, 11434],
 [1994, 5, 24, 2, 12562],
 [1994, 5, 25, 3, 12005],
 [1994, 5, 26, 4, 11979],
 [1994, 5, 27, 5, 12132],
 [1994, 5, 28, 6, 8840],
 [1994, 5, 29, 7, 8205],
 [1994, 5, 30, 1, 8468],
 [1994, 5, 31, 2, 11525],
 [1994, 6, 1, 3, 12349],
 [1994, 6, 2, 4, 12166],
 [1994, 6, 3, 5, 11799],
 [1994, 6, 4, 6, 9182],
 [1994, 6, 5, 7, 8289],
 [1994, 6, 6, 1, 11130],
 [1994, 6, 7, 2, 12145],
 [1994, 6, 8, 3, 11784],
 [1994, 6, 9, 4, 11648],
 [1994, 6, 10, 5, 12006],
 [1994, 6, 11, 6, 8618],
 [1994, 6, 12, 7, 8171],
 [1994, 6, 13, 1, 10692],
 [1994, 6, 14, 2, 12074],
 [1994, 6, 15, 3, 11954],
 [1994, 6, 16, 4, 11852],
 [1994, 6, 17, 5, 11744],
 [1994, 6, 18, 6, 8907],
 [1994, 6, 19, 7, 8302],
 [1994, 6, 20, 1, 11337],
 [1994, 6, 21, 2, 12182],
 [1994, 6, 22, 3, 12213],
 [1994, 6, 23, 4, 11939],
 [1994, 6, 24, 5, 11979],
 [1994, 6, 25, 6, 9047],
 [1994, 6, 26, 7, 8306],
 [1994, 6, 27, 1, 11309],
 [1994, 6, 28, 2, 12211],
 [1994, 6, 29, 3, 12245],
 [1994, 6, 30, 4, 12157],
 [1994, 7, 1, 5, 12454],
 [1994, 7, 2, 6, 9268],
 [1994, 7, 3, 7, 8298],
 [1994, 7, 4, 1, 8564],
 [1994, 7, 5, 2, 11609],
 [1994, 7, 6, 3, 13086],
 [1994, 7, 7, 4, 13049],
 [1994, 7, 8, 5, 12623],
 [1994, 7, 9, 6, 9325],
 [1994, 7, 10, 7, 8684],
 [1994, 7, 11, 1, 11567],
 [1994, 7, 12, 2, 12507],
 [1994, 7, 13, 3, 12134],
 [1994, 7, 14, 4, 12485],
 [1994, 7, 15, 5, 12691],
 [1994, 7, 16, 6, 9547],
 [1994, 7, 17, 7, 8848],
 [1994, 7, 18, 1, 11561],
 [1994, 7, 19, 2, 12583],
 [1994, 7, 20, 3, 12378],
 [1994, 7, 21, 4, 12447],
 [1994, 7, 22, 5, 12486],
 [1994, 7, 23, 6, 9463],
 [1994, 7, 24, 7, 8734],
 [1994, 7, 25, 1, 11757],
 [1994, 7, 26, 2, 12591],
 [1994, 7, 27, 3, 12423],
 [1994, 7, 28, 4, 12539],
 [1994, 7, 29, 5, 12231],
 [1994, 7, 30, 6, 9340],
 [1994, 7, 31, 7, 8590],
 [1994, 8, 1, 1, 11428],
 [1994, 8, 2, 2, 12622],
 [1994, 8, 3, 3, 12147],
 [1994, 8, 4, 4, 12601],
 [1994, 8, 5, 5, 12251],
 [1994, 8, 6, 6, 9336],
 [1994, 8, 7, 7, 8517],
 [1994, 8, 8, 1, 11528],
 [1994, 8, 9, 2, 12643],
 [1994, 8, 10, 3, 12525],
 [1994, 8, 11, 4, 12147],
 [1994, 8, 12, 5, 12479],
 [1994, 8, 13, 6, 9474],
 [1994, 8, 14, 7, 8926],
 [1994, 8, 15, 1, 11391],
 [1994, 8, 16, 2, 12605],
 [1994, 8, 17, 3, 12344],
 [1994, 8, 18, 4, 12313],
 [1994, 8, 19, 5, 12227],
 [1994, 8, 20, 6, 9646],
 [1994, 8, 21, 7, 8663],
 [1994, 8, 22, 1, 11489],
 [1994, 8, 23, 2, 12284],
 [1994, 8, 24, 3, 12176],
 [1994, 8, 25, 4, 12076],
 [1994, 8, 26, 5, 12122],
 [1994, 8, 27, 6, 9171],
 [1994, 8, 28, 7, 8779],
 [1994, 8, 29, 1, 11560],
 [1994, 8, 30, 2, 12431],
 [1994, 8, 31, 3, 12272],
 [1994, 9, 1, 4, 12183],
 [1994, 9, 2, 5, 12099],
 [1994, 9, 3, 6, 9042],
 [1994, 9, 4, 7, 8420],
 [1994, 9, 5, 1, 8378],
 [1994, 9, 6, 2, 11448],
 [1994, 9, 7, 3, 12660],
 [1994, 9, 8, 4, 12693],
 [1994, 9, 9, 5, 12811],
 [1994, 9, 10, 6, 9424],
 [1994, 9, 11, 7, 8373],
 [1994, 9, 12, 1, 11500],
 [1994, 9, 13, 2, 12560],
 [1994, 9, 14, 3, 12566],
 [1994, 9, 15, 4, 12655],
 [1994, 9, 16, 5, 12884],
 [1994, 9, 17, 6, 9779],
 [1994, 9, 18, 7, 8603],
 [1994, 9, 19, 1, 11659],
 [1994, 9, 20, 2, 12584],
 [1994, 9, 21, 3, 12468],
 [1994, 9, 22, 4, 12590],
 [1994, 9, 23, 5, 12522],
 [1994, 9, 24, 6, 9597],
 [1994, 9, 25, 7, 8754],
 [1994, 9, 26, 1, 11597],
 [1994, 9, 27, 2, 12591],
 [1994, 9, 28, 3, 12405],
 [1994, 9, 29, 4, 12288],
 [1994, 9, 30, 5, 12090],
 [1994, 10, 1, 6, 9351],
 [1994, 10, 2, 7, 8477],
 [1994, 10, 3, 1, 11437],
 [1994, 10, 4, 2, 12378],
 [1994, 10, 5, 3, 12061],
 [1994, 10, 6, 4, 12017],
 [1994, 10, 7, 5, 12050],
 [1994, 10, 8, 6, 8981],
 [1994, 10, 9, 7, 8038],
 [1994, 10, 10, 1, 11110],
 [1994, 10, 11, 2, 12236],
 [1994, 10, 12, 3, 11846],
 [1994, 10, 13, 4, 11398],
 [1994, 10, 14, 5, 11959],
 [1994, 10, 15, 6, 9077],
 [1994, 10, 16, 7, 8022],
 [1994, 10, 17, 1, 11127],
 [1994, 10, 18, 2, 11888],
 [1994, 10, 19, 3, 11533],
 [1994, 10, 20, 4, 11876],
 [1994, 10, 21, 5, 11562],
 [1994, 10, 22, 6, 9086],
 [1994, 10, 23, 7, 7914],
 [1994, 10, 24, 1, 11068],
 [1994, 10, 25, 2, 12019],
 [1994, 10, 26, 3, 11683],
 [1994, 10, 27, 4, 11420],
 [1994, 10, 28, 5, 11608],
 [1994, 10, 29, 6, 8855],
 [1994, 10, 30, 7, 8262],
 [1994, 10, 31, 1, 9833],
 [1994, 11, 1, 2, 12316],
 [1994, 11, 2, 3, 11736],
 [1994, 11, 3, 4, 11703],
 [1994, 11, 4, 5, 11956],
 [1994, 11, 5, 6, 8826],
 [1994, 11, 6, 7, 8100],
 [1994, 11, 7, 1, 11283],
 [1994, 11, 8, 2, 11999],
 [1994, 11, 9, 3, 11811],
 [1994, 11, 10, 4, 11728],
 [1994, 11, 11, 5, 11533],
 [1994, 11, 12, 6, 8672],
 [1994, 11, 13, 7, 8093],
 [1994, 11, 14, 1, 11044],
 [1994, 11, 15, 2, 11985],
 [1994, 11, 16, 3, 11634],
 [1994, 11, 17, 4, 11703],
 [1994, 11, 18, 5, 11826],
 [1994, 11, 19, 6, 8771],
 [1994, 11, 20, 7, 8133],
 [1994, 11, 21, 1, 11807],
 [1994, 11, 22, 2, 12764],
 [1994, 11, 23, 3, 11332],
 [1994, 11, 24, 4, 8036],
 [1994, 11, 25, 5, 9419],
 [1994, 11, 26, 6, 8427],
 [1994, 11, 27, 7, 7937],
 [1994, 11, 28, 1, 11003],
 [1994, 11, 29, 2, 12177],
 [1994, 11, 30, 3, 11643],
 [1994, 12, 1, 4, 11681],
 [1994, 12, 2, 5, 11379],
 [1994, 12, 3, 6, 8585],
 [1994, 12, 4, 7, 7980],
 [1994, 12, 5, 1, 10772],
 [1994, 12, 6, 2, 11923],
 [1994, 12, 7, 3, 11335],
 [1994, 12, 8, 4, 11337],
 [1994, 12, 9, 5, 11205],
 [1994, 12, 10, 6, 8461],
 [1994, 12, 11, 7, 7936],
 [1994, 12, 12, 1, 11106],
 [1994, 12, 13, 2, 11884],
 [1994, 12, 14, 3, 11716],
 [1994, 12, 15, 4, 11962],
 [1994, 12, 16, 5, 12144],
 [1994, 12, 17, 6, 8726],
 [1994, 12, 18, 7, 8130],
 [1994, 12, 19, 1, 11502],
 [1994, 12, 20, 2, 12880],
 [1994, 12, 21, 3, 12391],
 [1994, 12, 22, 4, 11504],
 [1994, 12, 23, 5, 10087],
 [1994, 12, 24, 6, 7898],
 [1994, 12, 25, 7, 7192],
 [1994, 12, 26, 1, 8454],
 [1994, 12, 27, 2, 11131],
 [1994, 12, 28, 3, 12398],
 [1994, 12, 29, 4, 12189],
 [1994, 12, 30, 5, 12051],
 [1994, 12, 31, 6, 8809],
 [1995, 1, 1, 7, 7828],
 [1995, 1, 2, 1, 7883],
 [1995, 1, 3, 2, 9999],
 [1995, 1, 4, 3, 11315],
 [1995, 1, 5, 4, 11243],
 [1995, 1, 6, 5, 11506],
 [1995, 1, 7, 6, 8681],
 [1995, 1, 8, 7, 7821],
 [1995, 1, 9, 1, 10434],
 [1995, 1, 10, 2, 11665],
 [1995, 1, 11, 3, 11279],
 [1995, 1, 12, 4, 11416],
 [1995, 1, 13, 5, 11071],
 [1995, 1, 14, 6, 8887],
 [1995, 1, 15, 7, 7988],
 [1995, 1, 16, 1, 10417],
 [1995, 1, 17, 2, 11345],
 [1995, 1, 18, 3, 11252],
 [1995, 1, 19, 4, 11331],
 [1995, 1, 20, 5, 11481],
 [1995, 1, 21, 6, 8746],
 [1995, 1, 22, 7, 7956],
 [1995, 1, 23, 1, 10640],
 [1995, 1, 24, 2, 11344],
 [1995, 1, 25, 3, 11096],
 [1995, 1, 26, 4, 11380],
 [1995, 1, 27, 5, 11340],
 [1995, 1, 28, 6, 8781],
 [1995, 1, 29, 7, 8009],
 [1995, 1, 30, 1, 10515],
 [1995, 1, 31, 2, 11364],
 [1995, 2, 1, 3, 11279],
 [1995, 2, 2, 4, 11490],
 [1995, 2, 3, 5, 11264],
 [1995, 2, 4, 6, 8769],
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 [1996, 9, 10, 2, 12662],
 [1996, 9, 11, 3, 12420],
 [1996, 9, 12, 4, 12486],
 [1996, 9, 13, 5, 12019],
 [1996, 9, 14, 6, 9323],
 [1996, 9, 15, 7, 8561],
 [1996, 9, 16, 1, 12107],
 [1996, 9, 17, 2, 13063],
 [1996, 9, 18, 3, 12630],
 [1996, 9, 19, 4, 12535],
 [1996, 9, 20, 5, 12754],
 [1996, 9, 21, 6, 9492],
 [1996, 9, 22, 7, 8694],
 [1996, 9, 23, 1, 11605],
 [1996, 9, 24, 2, 12910],
 [1996, 9, 25, 3, 12768],
 [1996, 9, 26, 4, 12684],
 ...]
In [ ]: