diff --git a/tutorial/Tutorial.ipynb b/tutorial/Tutorial.ipynb
index 1404b58..6c139e5 100644
--- a/tutorial/Tutorial.ipynb
+++ b/tutorial/Tutorial.ipynb
@@ -157,13 +157,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Today is 2018-12-20 08:25:03.511542\n",
+ "Today is 2018-12-20 19:23:32.779865\n",
"----------------------------------------------------------------\n",
"pandas version 0.23.4\n",
- "numpy version 1.15.0\n",
- "matplotlib version 2.2.2\n",
- "KDEpy version 0.5.6\n",
- "sklearn version 0.19.1\n"
+ "numpy version 1.15.3\n",
+ "matplotlib version 2.2.3\n",
+ "KDEpy version 0.6.9\n",
+ "sklearn version 0.20.0\n"
]
}
],
@@ -215,7 +215,17 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Too many parameters - -L\n"
+ "\u001b[01;34m.\u001b[00m\r\n",
+ "├── \u001b[01;34mdata\u001b[00m\r\n",
+ "│ ├── google_trends.csv\r\n",
+ "│ ├── movie_metadata.csv\r\n",
+ "│ ├── wine_data.csv\r\n",
+ "│ └── world_population_history.csv\r\n",
+ "├── \u001b[01;35mpandas_vs_excel_vs_sas.png\u001b[00m\r\n",
+ "├── Tutorial.ipynb\r\n",
+ "└── Tutorial.py\r\n",
+ "\r\n",
+ "1 directory, 7 files\r\n"
]
}
],
@@ -239,8 +249,10 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "color,director_name,num_critic_for_reviews,duration,director_facebook_likes,actor_3_facebook_likes,actor_2_name,actor_1_facebook_likes,gross,genres,actor_1_name,movie_title,num_voted_users,cast_total_facebook_likes,actor_3_name,facenumber_in_poster,plot_keywords,movie_imdb_link,num_user_for_reviews,language,country,content_rating,budget,title_year,actor_2_facebook_likes,imdb_score,aspect_ratio,movie_facebook_likes\n",
- "Color,James Cameron,723,178,0,855,Joel David Moore,1000,760505847,Action|Adventure|Fantasy|Sci-Fi,CCH Pounder,Avatar ,886204,4834,Wes Studi,0,avatar|future|marine|native|paraplegic,http://www.imdb.com/title/tt0499549/?ref_=fn_tt_tt_1,3054,English,USA,PG-13,237000000,2009,936,7.9,1.78,33000\n"
+ "color,director_name,num_critic_for_reviews,duration,director_facebook_likes,actor_3_facebook_likes,actor_2_name,actor_1_facebook_likes,gross,genres,actor_1_name,movie_title,num_voted_users,cast_total_facebook_likes,actor_3_name,facenumber_in_poster,plot_keywords,movie_imdb_link,num_user_for_reviews,language,country,content_rating,budget,title_year,actor_2_facebook_likes,imdb_score,aspect_ratio,movie_facebook_likes\r",
+ "\r\n",
+ "Color,James Cameron,723,178,0,855,Joel David Moore,1000,760505847,Action|Adventure|Fantasy|Sci-Fi,CCH Pounder,Avatar ,886204,4834,Wes Studi,0,avatar|future|marine|native|paraplegic,http://www.imdb.com/title/tt0499549/?ref_=fn_tt_tt_1,3054,English,USA,PG-13,237000000,2009,936,7.9,1.78,33000\r",
+ "\r\n"
]
}
],
@@ -266,7 +278,8 @@
"output_type": "stream",
"text": [
"Loaded data of size (5043, 6) into memory.\n",
- "Wall time: 72.8 ms\n"
+ "CPU times: user 70.3 ms, sys: 11.7 ms, total: 82.1 ms\n",
+ "Wall time: 143 ms\n"
]
}
],
@@ -472,7 +485,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
@@ -564,7 +577,7 @@
"4 18.1 billion Otto Group "
]
},
- "execution_count": 9,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -604,7 +617,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -637,7 +650,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 21,
"metadata": {},
"outputs": [
{
@@ -702,7 +715,7 @@
"1 USA PG-13 7.1 "
]
},
- "execution_count": 11,
+ "execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
@@ -727,7 +740,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 22,
"metadata": {},
"outputs": [
{
@@ -742,7 +755,7 @@
"dtype: object"
]
},
- "execution_count": 12,
+ "execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
@@ -753,7 +766,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 24,
"metadata": {},
"outputs": [
{
@@ -818,7 +831,7 @@
"1 21.3 billion Aldi Süd 21.3 "
]
},
- "execution_count": 13,
+ "execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
@@ -858,7 +871,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 25,
"metadata": {},
"outputs": [
{
@@ -923,7 +936,7 @@
"1 USA PG-13 7.1 "
]
},
- "execution_count": 14,
+ "execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
@@ -935,7 +948,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 26,
"metadata": {},
"outputs": [
{
@@ -969,38 +982,42 @@
" \n",
"
\n",
" \n",
- " 3882 | \n",
- " Richard Kwietniowski | \n",
- " 2542264.0 | \n",
- " Love and Death on Long Island | \n",
+ " 2375 | \n",
+ " Roger Donaldson | \n",
+ " 8600000.0 | \n",
+ " The Bounty | \n",
" UK | \n",
- " PG-13 | \n",
- " 7.1 | \n",
+ " PG | \n",
+ " 7.0 | \n",
"
\n",
" \n",
- " 448 | \n",
- " Mike Mitchell | \n",
- " 133103929.0 | \n",
- " Alvin and the Chipmunks: Chipwrecked | \n",
+ " 4252 | \n",
+ " Woody Allen | \n",
+ " NaN | \n",
+ " Everything You Always Wanted to Know About Sex... | \n",
" USA | \n",
- " G | \n",
- " 4.4 | \n",
+ " R | \n",
+ " 6.8 | \n",
"
\n",
" \n",
"\n",
""
],
"text/plain": [
- " director_name gross \\\n",
- "3882 Richard Kwietniowski 2542264.0 \n",
- "448 Mike Mitchell 133103929.0 \n",
+ " director_name gross \\\n",
+ "2375 Roger Donaldson 8600000.0 \n",
+ "4252 Woody Allen NaN \n",
"\n",
- " movie_title country content_rating imdb_score \n",
- "3882 Love and Death on Long Island UK PG-13 7.1 \n",
- "448 Alvin and the Chipmunks: Chipwrecked USA G 4.4 "
+ " movie_title country \\\n",
+ "2375 The Bounty UK \n",
+ "4252 Everything You Always Wanted to Know About Sex... USA \n",
+ "\n",
+ " content_rating imdb_score \n",
+ "2375 PG 7.0 \n",
+ "4252 R 6.8 "
]
},
- "execution_count": 15,
+ "execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
@@ -1025,7 +1042,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 27,
"metadata": {},
"outputs": [
{
@@ -1060,7 +1077,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 30,
"metadata": {},
"outputs": [
{
@@ -1075,7 +1092,7 @@
"dtype: int64"
]
},
- "execution_count": 17,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
@@ -1083,7 +1100,7 @@
"source": [
"# Detect missing values -> sum over rows\n",
"null_values = df.isnull().sum(axis=0)\n",
- "null_values"
+ "null_values # / len(df)"
]
},
{
@@ -1095,7 +1112,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 31,
"metadata": {},
"outputs": [
{
@@ -1104,7 +1121,7 @@
"pandas.core.series.Series"
]
},
- "execution_count": 18,
+ "execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
@@ -1130,7 +1147,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
@@ -1184,7 +1201,7 @@
"Missing values 0 "
]
},
- "execution_count": 19,
+ "execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
@@ -1202,7 +1219,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 33,
"metadata": {},
"outputs": [
{
@@ -1256,7 +1273,7 @@
"Missing values 0 "
]
},
- "execution_count": 20,
+ "execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
@@ -1283,7 +1300,7 @@
},
{
"cell_type": "code",
- "execution_count": 21,
+ "execution_count": 36,
"metadata": {},
"outputs": [
{
@@ -1338,7 +1355,7 @@
" top | \n",
" Steven Spielberg | \n",
" | \n",
- " The Fast and the Furious | \n",
+ " Pan | \n",
" USA | \n",
" R | \n",
" | \n",
@@ -1402,30 +1419,30 @@
""
],
"text/plain": [
- " director_name gross movie_title country \\\n",
- "count 4939 4159 5043 5038 \n",
- "unique 2398 4917 65 \n",
- "top Steven Spielberg The Fast and the Furious USA \n",
- "freq 26 3 3807 \n",
+ " director_name gross movie_title country content_rating \\\n",
+ "count 4939 4159 5043 5038 4740 \n",
+ "unique 2398 4917 65 18 \n",
+ "top Steven Spielberg Pan USA R \n",
+ "freq 26 3 3807 2118 \n",
"mean 4.84684e+07 \n",
"std 6.8453e+07 \n",
"min 162 \n",
"50% 2.55175e+07 \n",
"max 7.60506e+08 \n",
"\n",
- " content_rating imdb_score \n",
- "count 4740 5043 \n",
- "unique 18 \n",
- "top R \n",
- "freq 2118 \n",
- "mean 6.44214 \n",
- "std 1.12512 \n",
- "min 1.6 \n",
- "50% 6.6 \n",
- "max 9.5 "
+ " imdb_score \n",
+ "count 5043 \n",
+ "unique \n",
+ "top \n",
+ "freq \n",
+ "mean 6.44214 \n",
+ "std 1.12512 \n",
+ "min 1.6 \n",
+ "50% 6.6 \n",
+ "max 9.5 "
]
},
- "execution_count": 21,
+ "execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
@@ -1436,7 +1453,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 37,
"metadata": {},
"outputs": [
{
@@ -1445,7 +1462,7 @@
"(5043, 6)"
]
},
- "execution_count": 22,
+ "execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
@@ -1456,7 +1473,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 38,
"metadata": {},
"outputs": [
{
@@ -1465,7 +1482,7 @@
"(4092, 6)"
]
},
- "execution_count": 23,
+ "execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
@@ -1476,7 +1493,7 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 39,
"metadata": {},
"outputs": [
{
@@ -1485,7 +1502,7 @@
"(4920, 6)"
]
},
- "execution_count": 24,
+ "execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
@@ -1496,11 +1513,11 @@
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 40,
"metadata": {},
"outputs": [],
"source": [
- "df = df.dropna(axis=0, how='any')"
+ "df = df.dropna(axis=0, how='any').drop_duplicates(subset=None)"
]
},
{
@@ -1512,7 +1529,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 41,
"metadata": {},
"outputs": [
{
@@ -1522,7 +1539,7 @@
" 'Not Rated', 'M', 'GP', 'Passed'], dtype=object)"
]
},
- "execution_count": 26,
+ "execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
@@ -1533,7 +1550,7 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 44,
"metadata": {},
"outputs": [
{
@@ -1550,20 +1567,20 @@
},
{
"cell_type": "code",
- "execution_count": 28,
+ "execution_count": 47,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "R 1856\n",
- "PG-13 1400\n",
- "PG 611\n",
+ "R 1818\n",
+ "PG-13 1352\n",
+ "PG 596\n",
"G 95\n",
"Not Rated 56\n",
"Unrated 34\n",
"Approved 18\n",
- "X 10\n",
+ "X 9\n",
"NC-17 6\n",
"Passed 3\n",
"M 2\n",
@@ -1571,7 +1588,7 @@
"Name: content_rating, dtype: int64"
]
},
- "execution_count": 28,
+ "execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
@@ -1582,7 +1599,7 @@
},
{
"cell_type": "code",
- "execution_count": 29,
+ "execution_count": 48,
"metadata": {},
"outputs": [
{
@@ -1637,7 +1654,7 @@
"29 Jurassic World 652177271.0"
]
},
- "execution_count": 29,
+ "execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
@@ -1648,7 +1665,7 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 49,
"metadata": {},
"outputs": [
{
@@ -1746,7 +1763,7 @@
"1491 Aruba R 4.8 "
]
},
- "execution_count": 30,
+ "execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
@@ -1769,7 +1786,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 50,
"metadata": {},
"outputs": [
{
@@ -1800,25 +1817,25 @@
" \n",
" \n",
" gross | \n",
- " 1.000000 | \n",
- " 0.203786 | \n",
+ " 1.00000 | \n",
+ " 0.20497 | \n",
"
\n",
" \n",
" imdb_score | \n",
- " 0.203786 | \n",
- " 1.000000 | \n",
+ " 0.20497 | \n",
+ " 1.00000 | \n",
"
\n",
" \n",
"\n",
""
],
"text/plain": [
- " gross imdb_score\n",
- "gross 1.000000 0.203786\n",
- "imdb_score 0.203786 1.000000"
+ " gross imdb_score\n",
+ "gross 1.00000 0.20497\n",
+ "imdb_score 0.20497 1.00000"
]
},
- "execution_count": 31,
+ "execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
@@ -1829,17 +1846,19 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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UVU9V9UyYPHXsKpMkSRoDrQp4SeYB/wWYD1yQZHqHS5IkSRpzrQl4SULfTRbvq6ofAB8G/ndnq5IkSRp7rQl4wHuAH1TVt5r3fw68PMkJHaxJkiRpzLXmJouqWgIsGfB+M3Bk5yqSJEnqjNYEvO01Z8ZUei85tdNlSJIkjZo2naKVJEkSBjxJkqTWMeBJkiS1jAFPkiSpZQx4kiRJLWPAkyRJahkDniRJUssY8CRJklrGgCdJktQyBjxJkqSW6fpHla15eCOzFt/wvLZ1PrpMkiSNY87gSZIktcw2BbwkpyepJC/fWQWNliRPdLoGSZKkTtjWGby3AbcBZ47GxpN0/SliSZKk0TbigJdkCvArwLtpAl6SE5PckuQrSe5J8skkuzWfPZHk0iR3Jvm7JPs17Tcn+Z9J/h44P8kBzeerm9+/nGRqknUD+pqc5J+S7JHkpUm+nmRFklv7ZxOTHJhkWZLlSf5odIdJkiRp/NiWGbzTgK9X1XeBx5Mc0bQfDfx3YA7wUuBNTfsLgTur6gjg74E/GNDX3lV1QlVdCvwZcEVVzQWuBC6vqo3AKuCEZvlfA75RVT8DlgC/W1VHAhcCf94s81HgE1V1FPDP27BfkiRJrbItAe9twNLm9dLmPcAdVfVAVW0GrgaOa9r/Hbimef2XA9oZ0A7wSuCq5vUXByx3DfDW5vWZwDXNLOKxwJeSrAQ+BUxvlvmVZvv9/QwrycIkvUl6N2/auKVFJUmSxp0RXQOXZF/gNcDsJAVMAAr46+b3QIPfD9X+5BY217/c9cCfJNkHOBK4kb5ZwX+rqnkj2MbwG6haQt9MIHtOP3hE60iSJI0XI53BO4O+06gHVNWsqtofeJC+2bajm+vfdqNvxu22AX2f0bz+zQHtg/0DP79pY0H/clX1BHAHfadev1ZVm6vqx8CDSd4CkD6HNet+e1A/kiRJXWmkAe9twFcGtV1HX3BbBlwC3E1f6Otf7kng0CQr6Jv9+9AwfS8CfivJauAs4PwBn10DvJ3nn9JdALw7ySpgLfDGpv184Nwky4GpI9wvSZKk1knV9p+hTHIicGFVvWGIz56oqik7UNuY2HP6wTX9nZc9r80nWUiSpF1RkhVV1bO15br+e+jmzJhKr4FOkiS1yA4FvKq6Gbh5mM92+dk7SZKkNvJZtJIkSS1jwJMkSWoZA54kSVLLGPAkSZJaxoAnSZLUMgY8SZKkljHgSZIktYwBT5IkqWUMeJIkSS1jwJMkSWqZrn8W7ZqHNzJr8Q1bXW6dz6uVJEnjhDN4kiRJLTNqAS/JrCR3D2q7OMmFo9D33kneux3rjcr2JUmSxpNdZgYvyZZOF+8NbHPAkyRJ6kZjEvCS3JzkT5PckeS7SY5v2s9O8qUk/w/4ZpIpSf4uyZ1J1iR5Y9PFJcBLk6xM8uFm3fcnWZ5kdZI/HLCti5Lcl+RvgZeNxf5JkiTtSsbyJovdq+roJK8H/gD41ab9lcDcqnq8mcU7vap+nGQa8I9JrgcWA7Orah5AktcCBwNHAwGuT/Iq4EngTODwZt/uBFYMLiTJQmAhwIRf2m+n7bAkSVInjGbAq620f7n5vQKYNeDzb1XV483rAP+zCWv/DswAXjxEn69tfu5q3k+hL/DtBXylqjYBNOHwFwuqWgIsAdhz+sHD1S1JkjQujWbA2wC8aFDbPsCDzeunm9+bB233yQGvFwD7AUdW1c+SrAMmDrGtAH9SVZ96XmPyPoYPmpIkSV1h1K7Bq6ongEeTnASQZB/gdcBt29DNVOCHTbh7NXBA0/4T+mbn+n0DeFeSKc22ZiT5D8AtwOlJJiXZC/i1HdopSZKkcWi0r8F7B/DxJJc27/+wqr6fZKTrXwn8vyS9wErgOwBVtSHJt5uvYfmbqnp/klcAy5q+nwDeXlV3JrmmWfch4NZR2zNJkqRxIlXdfUZzz+kH1/R3XrbV5XyShSRJ6rQkK6qqZ2vLdf2jyubMmEqv4U2SJLXILvNFx5IkSRodBjxJkqSWMeBJkiS1jAFPkiSpZQx4kiRJLWPAkyRJahkDniRJUssY8CRJklrGgCdJktQyBjxJkqSW6fpHla15eCOzFt+w3ev7jFpJkrSrcQZPkiSpZQx4kiRJLbPVgJekklw64P2FSS7eyjqnJTlkmM8uTvJwkpVJ7knythHUMGx/W1nviW1dR5IkabwbyQze08Cbkkzbhn5PA7YUyD5SVfOANwKfSrLHDvYnSZKkxkgC3rPAEuCCwR8kOSDJ3yVZ3fz+5STHAr8OfLiZpXvpcB1X1f3AJuBFTX/vSbI8yaok1yWZPFR/zc/Xk6xIcmuSlzfrH5hkWdPHH23zaEiSJLXASK/B+ziwIMnUQe1/BlxRVXOBK4HLq+ofgOuB91fVvKr6/nCdJjkCuL+qftg0fbmqjqqqw4B7gXcP098S4Her6kjgQuDPm/U/Cnyiqo4C/nkL212YpDdJ7+ZNG0c4BJIkSePDiAJeVf0YuAJYNOijVwJXNa+/CBw3wu1ekOQ+4Hbg4gHts5sZuTXAAuDQwSsmmQIcC3wpyUrgU8D05uNfAa4eUM9w+7OkqnqqqmfC5MGZVZIkaXzblrtoLwPeDbxwC8vUCPv6SFW9DHgrcEWSiU3754HzqmoO8IfAxCHW3Q34t2Y2r//nFdtRgyRJUiuNOOBV1ePA/6Uv5PX7B+DM5vUC4Lbm9U+AvUbQ55eBXuCdTdNewKPNTRcLBiz6XH/NbOKDSd4CkD6HNct9e1A9kiRJXWdbvwfvUmDg3bSLgN9Ksho4Czi/aV8KvD/JXVu6yaLxIeC/JdkN+H36Ttt+C/jOgGUG97cAeHeSVcBa+u7Gpdn+uUmWA557lSRJXSlV3X1Gc8/pB9f0d1623ev7qDJJkjRWkqyoqp6tLdf1z6KdM2MqvYY0SZLUIj6qTJIkqWUMeJIkSS1jwJMkSWoZA54kSVLLGPAkSZJaxoAnSZLUMgY8SZKkljHgSZIktYwBT5IkqWUMeJIkSS3T9Y8qW/PwRmYtvmFMtuVzayVJ0lhwBk+SJKllWhXwkrw4yVVJHkiyIsmyJKd3ui5JkqSx1JqAlyTAV4FbquqgqjoSOBOY2dnKJEmSxlabrsF7DfBMVX2yv6GqHgI+1rmSJEmSxl5rZvCAQ4E7O12EJElSp7Up4D1Pko8nWZVk+RCfLUzSm6R386aNnShPkiRpp2lTwFsLHNH/pqrOBU4C9hu8YFUtqaqequqZMHnqGJYoSZK087Up4N0ITEzyOwPaJneqGEmSpE5pTcCrqgJOA05I8mCSO4AvAB/obGWSJEljq0130VJVj9L31SiSJEldq1UBb3vMmTGVXh8hJkmSWqQ1p2glSZLUx4AnSZLUMgY8SZKkljHgSZIktYwBT5IkqWUMeJIkSS1jwJMkSWoZA54kSVLLGPAkSZJaxoAnSZLUMgY8SZKklun6Z9GueXgjsxbf0OkypG22zmcoS5KG4QyeJElSy4y7gJdkc5KVSe5O8qUkk5v2Fye5KskDSVYkWZbk9E7XK0mSNNbGXcADnqqqeVU1G3gGOCdJgK8Ct1TVQVV1JHAmMLOThUqSJHXCeAx4A90K/CfgNcAzVfXJ/g+q6qGq+ljHKpMkSeqQcRvwkuwOnAKsAQ4F7tyGdRcm6U3Su3nTxp1VoiRJUkeMx4A3KclKoBf4AfCZwQsk+XiSVUmWD9VBVS2pqp6q6pkweepOLleSJGlsjcevSXmqquYNbEiyFnhz//uqOjfJNPpCoCRJUlcZjzN4Q7kRmJjkdwa0Te5UMZIkSZ3UioBXVQWcBpyQ5MEkdwBfAD7Q2cokSZLG3rg7RVtVU4Zpf5S+r0aRJEnqauMu4I22OTOm0usjnyRJUou04hStJEmSfs6AJ0mS1DIGPEmSpJYx4EmSJLWMAU+SJKllDHiSJEktY8CTJElqGQOeJElSyxjwJEmSWsaAJ0mS1DJd/6iyNQ9vZNbiGzpdhiRpHFrnoy61i3IGT5IkqWUMeJIkSS0z5gEvyeYkK5PcneRLSSY37S9OclWSB5KsSLIsyenD9PGWJGuT/HuSngHtRzd9r0yyarj1JUmS2qwTM3hPVdW8qpoNPAOckyTAV4FbquqgqjoSOBOYOUwfdwNvAm4Zor2nquYBrwM+laTrrzOUJEndpdPh51ZgLvAa4Jmq+mT/B1X1EPCxoVaqqnsB+nLh89o3DXg7EahRrleSJGmX17Fr8JqZtVOANcChwJ2j1O8xSdY2/Z5TVc8OsczCJL1Jejdv2jgam5UkSdpldCLgTUqyEugFfgB8ZvACST7eXEO3fFs7r6rbq+pQ4Cjg95JMHGKZJVXVU1U9EyZP3Y5dkCRJ2nV14hTtU801cs9pZtze3P++qs5NMo2+EEiSzwGHA49U1etHspGqujfJk8Ds/n4kSZK6wa7yNSk3AhOT/M6Atsn9L6rqt5obM7YY7pIc2H9TRZIDgJcB63ZCvZIkSbusXSLgVVUBpwEnJHkwyR3AF4APDLV8ktOTrAdeCdyQ5BvNR8cBq5pTwF8B3ltV/7Lz90CSJGnXkb5s1b16enqqt9czuJIkadeXZEVV9WxtuV1iBk+SJEmjx4AnSZLUMgY8SZKkljHgSZIktYwBT5IkqWUMeJIkSS1jwJMkSWoZA54kSVLLGPAkSZJaxoAnSZLUMgY8SZKkltm90wV02pqHNzJr8Q2dLkOSJI1j6y45tdMlPI8zeJIkSS3Tqhm8JJuBNfTt14PAWVX1b52tSpIkaWy1bQbvqaqaV1WzgceBcztdkCRJ0lhrW8AbaBkwo9NFSJIkjbVWBrwkE4CTgOuH+Xxhkt4kvZs3bRzb4iRJknaytgW8SUlWAhuAfYBvDbVQVS2pqp6q6pkweeqYFihJkrSztS3gPVVV84ADgBfgNXiSJKkLtS3gAVBVG4FFwIVJ9uh0PZIkSWOplQEPoKruAlYBZ3a6FkmSpLHUqu/Bq6opg97/WqdqkSRJ6pRWBbztMWfGVHp3sceLSJIk7YjWnqKVJEnqVgY8SZKkljHgSZIktYwBT5IkqWUMeJIkSS2Tqup0DR2V5CfAfZ2uYxc2DfiXThexi3JstszxGZ5js2WOz5Y5PsPrhrE5oKr229pCXf81KcB9VdXT6SJ2VUl6HZ+hOTZb5vgMz7HZMsdnyxyf4Tk2P+cpWkmSpJYx4EmSJLWMAQ+WdLqAXZzjMzzHZsscn+E5Nlvm+GyZ4zM8x6bR9TdZSJIktY0zeJIkSS1jwJMkSWqZrg54SV6X5L4k30uyuNP1jLUk+ye5Kcm9SdYmOb9pvzjJw0lWNj+vH7DO7zXjdV+SkztX/dhIsi7JmmYcepu2fZJ8K8n9ze8XNe1JcnkzPquTHNHZ6neeJC8bcHysTPLjJO/r5mMnyWeT/DDJ3QPatvlYSfLOZvn7k7yzE/sy2oYZmw8n+U6z/19JsnfTPivJUwOOoU8OWOfI5u/xe834pRP7M9qGGZ9t/ltq679pw4zPNQPGZl2SlU171x0/w6qqrvwBJgDfBw4CXgCsAg7pdF1jPAbTgSOa13sB3wUOAS4GLhxi+UOacdoTOLAZvwmd3o+dPEbrgGmD2v4XsLh5vRj40+b164G/AQLMB27vdP1jNEYTgH8GDujmYwd4FXAEcPf2HivAPsADze8XNa9f1Ol920lj81pg9+b1nw4Ym1kDlxvUzx3AK5tx+xvglE7v204cn236W2rzv2lDjc+gzy8FPtitx89wP908g3c08L2qeqCqngGWAm/scE1jqqoerao7m9c/Ae4FZmxhlTcCS6vq6ap6EPgefePYbd4IfKF5/QXgtAHtV1SffwT2TjK9EwWOsZOA71fVQ1tYpvXHTlXdAjw+qHlbj5WTgW9V1eNV9a/At4DX7fzqd66hxqaqvllVzzZv/xGYuaU+mvH5papaVn3/Wl/Bz8dzXBvm2BnOcH9Lrf03bUvj08zC/QZw9Zb6aPPxM5xuDngzgH8a8H49Ww43rZZkFnA4cHvTdF5z6uSz/aeV6M4xK+CbSVYkWdi0vbiqHoW+kAz8h6a9G8cH4Eye/x9Xj52f29ZjpVvH6V30zaj0OzDJXUn+PsnxTdsM+sajXzeMzbb8LXXrsXM88FhV3T+gzeOH7g54Q51DCegsAAACkUlEQVR778rvjEkyBbgOeF9V/Rj4BPBSYB7wKH3T39CdY/YrVXUEcApwbpJXbWHZrhufJC8Afh34UtPksTMyw41H141TkouAZ4Erm6ZHgV+uqsOB/wZcleSX6L6x2da/pW4bn35v4/n/B9Pjp9HNAW89sP+A9zOBRzpUS8ck2YO+cHdlVX0ZoKoeq6rNVfXvwKf5+am0rhuzqnqk+f1D4Cv0jcVj/adem98/bBbvuvGhL/jeWVWPgcfOELb1WOmqcWpuInkDsKA5bUZz6nFD83oFfdeV/Wf6xmbgadxWj812/C111bEDkGR34E3ANf1tHj8/180BbzlwcJIDm1mIM4HrO1zTmGquXfgMcG9V/Z8B7QOvGzsd6L9z6XrgzCR7JjkQOJi+i1ZbKckLk+zV/5q+i8Lvpm8c+u9ufCfwV83r64F3NHdIzgc29p+ea7Hn/b9nj51fsK3HyjeA1yZ5UXNK7rVNW+skeR3wAeDXq2rTgPb9kkxoXh9E37HyQDM+P0kyv/lv1zv4+Xi2znb8LXXjv2m/Cnynqp479erxM0Cn7/Lo5A99d7J9l76Ef1Gn6+nA/h9H3xT1amBl8/N64IvAmqb9emD6gHUuasbrPlp+BxJ9d6Otan7W9h8jwL7A3wH3N7/3adoDfLwZnzVAT6f3YSePz2RgAzB1QFvXHjv0Bd1HgZ/RN1vw7u05Vui7Hu17zc9vdXq/duLYfI++a8b6/9vzyWbZNzd/b6uAO4FfG9BPD31B5/vAn9E8jWm8/wwzPtv8t9TWf9OGGp+m/fPAOYOW7brjZ7gfH1UmSZLUMt18ilaSJKmVDHiSJEktY8CTJElqGQOeJElSyxjwJEmSWsaAJ0mS1DIGPEmSpJb5/3kFS7opYyZRAAAAAElFTkSuQmCC\n",
+ "image/png": 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\n",
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