Commit Live PR

data/scrapeddata.csv

@@ -0,0 +1,78 @@
+,0,1,2,3,4,5,6,7,8,9,10,11,12,13,14
+11,United States of America,Federal state,".mw-parser-output .monospaced{font-family:monospace,monospace}USUSA840",US,00,,,U.S.,U.S.,U.S.A.,,,,,
+12,Alabama,State,US-AL,AL,01,AL,AL,Ala.,Ala.,,,,,,
+13,Alaska,State,US-AK,AK,02,AK,AK,Alaska,Alaska,Alas.,,,,,
+14,Arizona,State,US-AZ,AZ,04,AZ,AZ,Ariz.,Ariz.,Az.,,,,,
+15,Arkansas,State,US-AR,AR,05,AR,AR,Ark.,Ark.,,,,,,
+16,California,State,US-CA,CA,06,CA,CF,Calif.,Calif.,"Ca., Cal.",,,,,
+17,Colorado,State,US-CO,CO,08,CO,CL,Colo.,Colo.,Col.,,,,,
+18,Connecticut,State,US-CT,CT,09,CT,CT,Conn.,Conn.,Ct.,,,,,
+19,Delaware,State,US-DE,DE,10,DE,DL,Del.,Del.,De.,,,,,
+20,District of Columbia,Federal district,US-DC,DC,11,DC,DC,D.C.,D.C.,Wash. D.C.,,,,,
+21,Florida,State,US-FL,FL,12,FL,FL,Fla.,Fla.,"Fl., Flor.",,,,,
+22,Georgia,State,US-GA,GA,13,GA,GA,Ga.,Ga.,Geo.,,,,,
+23,Hawaii,State,US-HI,HI,15,HI,HA,Hawaii,Hawaii,H.I.,,,,,
+24,Idaho,State,US-ID,ID,16,ID,ID,Idaho,Idaho,"Id., Ida.",,,,,
+25,Illinois,State,US-IL,IL,17,IL,IL,Ill.,Ill.,"Il., Ills., Ill's",,,,,
+26,Indiana,State,US-IN,IN,18,IN,IN,Ind.,Ind.,In.,,,,,
+27,Iowa,State,US-IA,IA,19,IA,IA,Iowa,Iowa,"Ia., Ioa.[1]",,,,,
+28,Kansas,State,US-KS,KS,20,KS,KA,Kans.,Kan.,"Ks., Ka.",,,,,
+29,Kentucky,State (Commonwealth),US-KY,KY,21,KY,KY,Ky.,Ky.,"Ken., Kent.",,,,,
+30,Louisiana,State,US-LA,LA,22,LA,LA,La.,La.,,,,,,
+31,Maine,State,US-ME,ME,23,ME,ME,Maine,Maine,Me.,,,,,
+32,Maryland,State,US-MD,MD,24,MD,MD,Md.,Md.,,,,,,
+33,Massachusetts,State (Commonwealth),US-MA,MA,25,MA,MS,Mass.,Mass.,,,,,,
+34,Michigan,State,US-MI,MI,26,MI,MC,Mich.,Mich.,,,,,,
+35,Minnesota,State,US-MN,MN,27,MN,MN,Minn.,Minn.,Mn.,,,,,
+36,Mississippi,State,US-MS,MS,28,MS,MI,Miss.,Miss.,,,,,,
+37,Missouri,State,US-MO,MO,29,MO,MO,Mo.,Mo.,,,,,,
+38,Montana,State,US-MT,MT,30,MT,MT,Mont.,Mont.,,,,,,
+39,Nebraska,State,US-NE,NE,31,NE,NB,Nebr.,Neb.,,,,,,
+40,Nevada,State,US-NV,NV,32,NV,NV,Nev.,Nev.,Nv.,,,,,
+41,New Hampshire,State,US-NH,NH,33,NH,NH,N.H.,N.H.,,,,,,
+42,New Jersey,State,US-NJ,NJ,34,NJ,NJ,N.J.,N.J.,N.Jersey,,,,,
+43,New Mexico,State,US-NM,NM,35,NM,NM,N. Mex.,N.M.,New M.,,,,,
+44,New York,State,US-NY,NY,36,NY,NY,N.Y.,N.Y.,N. York,,,,,
+45,North Carolina,State,US-NC,NC,37,NC,NC,N.C.,N.C.,N. Car.,,,,,
+46,North Dakota,State,US-ND,ND,38,ND,ND,N. Dak.,N.D.,NoDak,,,,,
+47,Ohio,State,US-OH,OH,39,OH,OH,Ohio,Ohio,"O., Oh.",,,,,
+48,Oklahoma,State,US-OK,OK,40,OK,OK,Okla.,Okla.,Ok.,,,,,
+49,Oregon,State,US-OR,OR,41,OR,OR,Oreg.,Ore.,Or.,,,,,
+50,Pennsylvania,State (Commonwealth),US-PA,PA,42,PA,PA,Pa.,Pa.,"Penn., Penna.",,,,,
+51,Rhode Island,State,US-RI,RI,44,RI,RI,R.I.,R.I.,"R.I. & P.P., R. Isl.",,,,,
+52,South Carolina,State,US-SC,SC,45,SC,SC,S.C.,S.C.,S. Car.,,,,,
+53,South Dakota,State,US-SD,SD,46,SD,SD,S. Dak.,S.D.,SoDak,,,,,
+54,Tennessee,State,US-TN,TN,47,TN,TN,Tenn.,Tenn.,,,,,,
+55,Texas,State,US-TX,TX,48,TX,TX,Tex.,Texas,Tx.,,,,,
+56,Utah,State,US-UT,UT,49,UT,UT,Utah,Utah,Ut.,,,,,
+57,Vermont,State,US-VT,VT,50,VT,VT,Vt.,Vt.,,,,,,
+58,Virginia,State (Commonwealth),US-VA,VA,51,VA,VA,Va.,Va.,Virg.,,,,,
+59,Washington,State,US-WA,WA,53,WA,WN,Wash.,Wash.,"Wa., Wn.[2]",,,,,
+60,West Virginia,State,US-WV,WV,54,WV,WV,W. Va.,W.Va.,"W.V., W. Virg.",,,,,
+61,Wisconsin,State,US-WI,WI,55,WI,WS,Wis.,Wis.,"Wi., Wisc.",,,,,
+62,Wyoming,State,US-WY,WY,56,WY,WY,Wyo.,Wyo.,Wy.,,,,,
+63,American Samoa,Insular area (Territory),ASASM016US-AS,AS,60,AS,AS,A.S.,,,,,,,
+64,Guam,Insular area (Territory),GUGUM316US-GU,GU,66,GU,GU,Guam,,,,,,,
+65,Northern Mariana Islands,Insular area (Commonwealth),MPMNP580US-MP,MP,69,MP,CM,M.P.,,CNMI[3],,,,,
+66,Puerto Rico,Insular area (Territory),PRPRI630US-PR,PR,72,PR,PR,P.R.,,,,,,,
+67,U.S. Virgin Islands,Insular area (Territory),VIVIR850US-VI,VI,78,VI,VI,V.I.,,U.S.V.I.,,,,,
+68,U.S. Minor Outlying Islands,Insular areas,UMUMI581US-UM,UM,74,,,,,,,,,,
+69,Baker Island,island,UM-81,,81,,,,,XB[4],,,,,
+70,Howland Island,island,UM-84,,84,,,,,XH[4],,,,,
+71,Jarvis Island,island,UM-86,,86,,,,,XQ[4],,,,,
+72,Johnston Atoll,atoll,UM-67,,67,,,,,XU[4],,,,,
+73,Kingman Reef,atoll,UM-89,,89,,,,,XM[4],,,,,
+74,Midway Islands,atoll,UM-71,,71,,,,,QM[4],,,,,
+75,Navassa Island,island,UM-76,,76,,,,,XV[4],,,,,
+76,Palmyra Atoll[5],atoll[5],UM-95,,95,,,,,XL[4],,,,,
+77,Wake Island,atoll,UM-79,,79,,,,,QW[4],,,,,
+78,Micronesia,Freely associated state,FMFSM583,FM,64,FM,,,,,,,,,
+79,Marshall Islands,Freely associated state,MHMHL584,MH,68,MH,,,,,,,,,
+80,Palau,Freely associated state,PWPLW585,PW,70,PW,,,,,,,,,
+81,U.S. Armed Forces – Americas[6],US military mail code,,,,AA,,,,,,,,,
+82,U.S. Armed Forces – Europe[7],US military mail code,,,,AE,,,,,,,,,
+83,U.S. Armed Forces – Pacific[8],US military mail code,,,,AP,,,,,,,,,
+84,Northern Mariana Islands,Obsolete postal code[9],,,,CM,,,,,,,,,
+85,Panama Canal Zone,Obsolete postal code,PZPCZ594,,,CZ,,,,,,,,,
+86,Nebraska,Obsolete postal code[10],,,,NB,,,,,,,,,
+87,Philippine Islands,Obsolete postal code,PHPHL608[11],,,PI,,,,,,,,,

q01_load_data/build.py

@@ -1,5 +1,15 @@
+# %load q01_load_data/build.py
 import pandas as pd
 
+path = './data/excel-comp-data.xlsx'
 
 def q01_load_data(path):
-    "write your solution here"
+    df = pd.read_excel(path)
+    df['state'] = df['state'].str.lower()
+    df['total'] = df['Jan'] + df['Feb'] + df['Mar']
+    return df
+
+
+
+
+

q02_append_row/build.py

@@ -1,11 +1,29 @@
+# %load q02_append_row/build.py
 import pandas as pd
 import sys, os
 #sys.path.append(os.path.join(os.path.dirname(os.curdir)))
 from greyatomlib.pandas_guided_project.q01_load_data.build import q01_load_data
 
+path = './data/excel-comp-data.xlsx'
 
 def q02_append_row(path):
-    "write your solution here"
+    df = q01_load_data(path)
+    total_jan = df['Jan'].sum()
+    total_feb = df['Feb'].sum()
+    total_mar = df['Mar'].sum()
+    total_grand = df['total'].sum()
+
+    df2 = pd.DataFrame(columns= df.columns)
+    df2['Jan'] = [total_jan]
+    df2['Feb'] = [total_feb]
+    df2['Mar'] = [total_mar]
+    df2['total'] = [total_grand]
+    df = df.append(df2, ignore_index=True)
+    return df
+
+
+
+
 
 
 

q03_scrape_clean/build.py

@@ -1,9 +1,22 @@
+# %load q03_scrape_clean/build.py
 import pandas as pd
 import sys, os
 import requests
 sys.path.append(os.path.join(os.path.dirname(os.curdir)))
 
 
+
 def q03_scrape_clean(url):
-    "write your solution here"
+    data = requests.get(url)
+    mlist = pd.read_html(data.text)
+    df = mlist[0]
+    df = df[11:-1]
+    df.to_csv('./data/scrapeddata.csv')
+    return df
+
+
+
+
+
+
 

q04_mapping/build.py

@@ -1,10 +1,34 @@
+# %load q04_mapping/build.py
 import pandas as pd
 import sys, os
 import numpy as np
 #sys.path.append(os.path.join(os.path.dirname(os.curdir)))
 from greyatomlib.pandas_guided_project.q02_append_row.build import q02_append_row
+from greyatomlib.pandas_guided_project.q03_scrape_clean.build import q03_scrape_clean
+
+
+path1 = './data/excel-comp-data.xlsx'
+path2 = './data/scraped.csv'
+
 def q04_mapping(path1,path2):
-    "write your solution here"
+    'write your solution here'
+    df = pd.read_csv(path2)
+    namesList =  df['United States of America'].values
+    abbrList = df['US'].values
+    zippedList = list(zip(namesList, abbrList))
+    mapping = dict(zippedList)
+
+    df = pd.read_excel(path1)
+    abbr = list()
+    for state in df['state'].values:
+        if state in mapping.keys() : abbr.append(mapping[state])
+        else : abbr.append(np.nan)
+    pd.Series(abbr)
+
+    df.insert(6, 'abbr', abbr)
+    return df
+
+
 
 
 

q05_replace_missing_values/build.py

@@ -1,13 +1,42 @@
+# %load q05_replace_missing_values/build.py
 import pandas as pd
 import numpy as np
 import sys
 import os
-#sys.path.append(os.path.join(os.path.dirname(os.curdir)))
-from greyatomlib.pandas_guided_project.q04_mapping.build import q04_mapping
+# sys.path.append(os.path.join(os.path.dirname(os.curdir)))
+# from greyatomlib.pandas_guided_project.q04_mapping.build import q04_mapping
+
+path1 = '/home/notebooks/data/excel-comp-data.xlsx'
+path2 = '/home/notebooks/data/scraped.csv'
+
+def q04_mapping(path1,path2):
+    'write your solution here'
+    df = pd.read_csv(path2)
+    namesList =  df['United States of America'].values
+    abbrList = df['US'].values
+    zippedList = list(zip(namesList, abbrList))
+    mapping = dict(zippedList)
+
+    df = pd.read_excel(path1)
+    abbr = list()
+    for state in df['state'].values:
+        if state in mapping.keys() : abbr.append(mapping[state])
+        else : abbr.append(np.nan)
+    pd.Series(abbr)
+
+    df.insert(6, 'abbr', abbr)
+    return df
 
-path1 = 'data/excel-comp-data.xlsx'
-path2 = 'data/scraped.csv'
 def q05_replace_missing_values(path1,path2):
+    df = q04_mapping(path1, path2)
+    df.at[6, 'abbr'] = 'MS'
+    df.at[10, 'abbr'] = 'TN'
+    return df
+
+
+
+
+
+
 
 
-#print(q05_replace_missing_values(path1,path2).shape)

q06_sub_total/build.py

@@ -1,16 +1,43 @@
+# %load q06_sub_total/build.py
 import pandas as pd
 import numpy as np
 from sklearn.model_selection import train_test_split
 import sys
 import os
-#sys.path.append(os.path.join(os.path.dirname(os.curdir)))
+sys.path.append(os.path.join(os.path.dirname(os.curdir)))
 from greyatomlib.pandas_guided_project.q05_replace_missing_values.build import q05_replace_missing_values
 
-path1 = 'data/excel-comp-data.xlsx'
-path2 = 'data/scraped.csv'
+
+def q04_mapping(path1,path2):
+    'write your solution here'
+    df = pd.read_csv(path2)
+    namesList =  df['United States of America'].values
+    abbrList = df['US'].values
+    zippedList = list(zip(namesList, abbrList))
+    mapping = dict(zippedList)
+
+    df = pd.read_excel(path1)
+    abbr = list()
+    for state in df['state'].values:
+        if state in mapping.keys() : abbr.append(mapping[state])
+        else : abbr.append(np.nan)
+    pd.Series(abbr)
+
+    df.insert(6, 'abbr', abbr)
+    return df
+
+def q05_replace_missing_values(path1,path2):
+    df = q04_mapping(path1, path2)
+    df.at[6, 'abbr'] = 'MS'
+    df.at[10, 'abbr'] = 'TN'
+    return df
 
 def q06_sub_total(path1,path2):
-    "write your solution here"
+    'write your solution here'
+    df = q05_replace_missing_values(path1, path2)
+    df = df.groupby(['abbr']).sum()
+    df = df[['account', 'Jan', 'Feb', 'Mar']]
+    return df
 
 
 

q07_symbols/build.py

@@ -1,18 +1,55 @@
+# %load q07_symbols/build.py
 import pandas as pd
 import numpy as np
 from sklearn.model_selection import train_test_split
 import sys
 import os
+import locale
 sys.path.append(os.path.join(os.path.dirname(os.curdir)))
-from greyatomlib.pandas_guided_project.q06_sub_total.build import q06_sub_total
+# from greyatomlib.pandas_guided_project.q06_sub_total.build import q06_sub_total
 
 path1 = 'data/excel-comp-data.xlsx'
 path2 = 'data/scraped.csv'
 
+def q04_mapping(path1,path2):
+    'write your solution here'
+    df = pd.read_csv(path2)
+    namesList =  df['United States of America'].values
+    abbrList = df['US'].values
+    zippedList = list(zip(namesList, abbrList))
+    mapping = dict(zippedList)
+
+    df = pd.read_excel(path1)
+    abbr = list()
+    for state in df['state'].values:
+        if state in mapping.keys() : abbr.append(mapping[state])
+        else : abbr.append(np.nan)
+    pd.Series(abbr)
+
+    df.insert(6, 'abbr', abbr)
+    return df
+
+def q05_replace_missing_values(path1,path2):
+    df = q04_mapping(path1, path2)
+    df.at[6, 'abbr'] = 'MS'
+    df.at[10, 'abbr'] = 'TN'
+    return df
+
+def q06_sub_total(path1,path2):
+    'write your solution here'
+    df = q05_replace_missing_values(path1, path2)
+    df = df.groupby(['abbr']).sum()
+    df = df[['account', 'Jan', 'Feb', 'Mar']]
+    return df
+
+
 def q07_symbols(path1,path2):
-    "write your solution here"
+    'write your solution here'
+    df = q06_sub_total(path1, path2)
+    df['total'] = df['Jan'] + df['Feb'] + df['Mar']
+    df = df.applymap(lambda x : '$' + '{:2,}'.format(x))
+    return df
 
 
 
-#print(q07_symbols(path1,path2))