Skip to content

Commit ba4addf

Browse files
KaranKumar-55KaranKumar-55
authored
Add files via upload
1 parent 46267a0 commit ba4addf

File tree

1 file changed

+199
-0
lines changed

1 file changed

+199
-0
lines changed

‎covid.ipynb

+199
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,199 @@
1+
{
2+
"cells": [
3+
{
4+
"cell_type": "code",
5+
"execution_count": 1,
6+
"metadata": {},
7+
"outputs": [
8+
{
9+
"data": {
10+
"text/html": [
11+
"<div>\n",
12+
"<style scoped>\n",
13+
" .dataframe tbody tr th:only-of-type {\n",
14+
" vertical-align: middle;\n",
15+
" }\n",
16+
"\n",
17+
" .dataframe tbody tr th {\n",
18+
" vertical-align: top;\n",
19+
" }\n",
20+
"\n",
21+
" .dataframe thead th {\n",
22+
" text-align: right;\n",
23+
" }\n",
24+
"</style>\n",
25+
"<table border=\"1\" class=\"dataframe\">\n",
26+
" <thead>\n",
27+
" <tr style=\"text-align: right;\">\n",
28+
" <th></th>\n",
29+
" <th>id</th>\n",
30+
" <th>neutral_venue</th>\n",
31+
" <th>result_margin</th>\n",
32+
" <th>method</th>\n",
33+
" </tr>\n",
34+
" </thead>\n",
35+
" <tbody>\n",
36+
" <tr>\n",
37+
" <th>count</th>\n",
38+
" <td>2.100000e+01</td>\n",
39+
" <td>21.0</td>\n",
40+
" <td>20.000000</td>\n",
41+
" <td>0.0</td>\n",
42+
" </tr>\n",
43+
" <tr>\n",
44+
" <th>mean</th>\n",
45+
" <td>1.254068e+06</td>\n",
46+
" <td>0.0</td>\n",
47+
" <td>14.100000</td>\n",
48+
" <td>NaN</td>\n",
49+
" </tr>\n",
50+
" <tr>\n",
51+
" <th>std</th>\n",
52+
" <td>6.204837e+00</td>\n",
53+
" <td>0.0</td>\n",
54+
" <td>17.001238</td>\n",
55+
" <td>NaN</td>\n",
56+
" </tr>\n",
57+
" <tr>\n",
58+
" <th>min</th>\n",
59+
" <td>1.254058e+06</td>\n",
60+
" <td>0.0</td>\n",
61+
" <td>2.000000</td>\n",
62+
" <td>NaN</td>\n",
63+
" </tr>\n",
64+
" <tr>\n",
65+
" <th>25%</th>\n",
66+
" <td>1.254063e+06</td>\n",
67+
" <td>0.0</td>\n",
68+
" <td>6.000000</td>\n",
69+
" <td>NaN</td>\n",
70+
" </tr>\n",
71+
" <tr>\n",
72+
" <th>50%</th>\n",
73+
" <td>1.254068e+06</td>\n",
74+
" <td>0.0</td>\n",
75+
" <td>8.000000</td>\n",
76+
" <td>NaN</td>\n",
77+
" </tr>\n",
78+
" <tr>\n",
79+
" <th>75%</th>\n",
80+
" <td>1.254073e+06</td>\n",
81+
" <td>0.0</td>\n",
82+
" <td>10.750000</td>\n",
83+
" <td>NaN</td>\n",
84+
" </tr>\n",
85+
" <tr>\n",
86+
" <th>max</th>\n",
87+
" <td>1.254078e+06</td>\n",
88+
" <td>0.0</td>\n",
89+
" <td>69.000000</td>\n",
90+
" <td>NaN</td>\n",
91+
" </tr>\n",
92+
" </tbody>\n",
93+
"</table>\n",
94+
"</div>"
95+
],
96+
"text/plain": [
97+
" id neutral_venue result_margin method\n",
98+
"count 2.100000e+01 21.0 20.000000 0.0\n",
99+
"mean 1.254068e+06 0.0 14.100000 NaN\n",
100+
"std 6.204837e+00 0.0 17.001238 NaN\n",
101+
"min 1.254058e+06 0.0 2.000000 NaN\n",
102+
"25% 1.254063e+06 0.0 6.000000 NaN\n",
103+
"50% 1.254068e+06 0.0 8.000000 NaN\n",
104+
"75% 1.254073e+06 0.0 10.750000 NaN\n",
105+
"max 1.254078e+06 0.0 69.000000 NaN"
106+
]
107+
},
108+
"execution_count": 1,
109+
"metadata": {},
110+
"output_type": "execute_result"
111+
}
112+
],
113+
"source": [
114+
"import pandas as pd\n",
115+
"from pandas_profiling import ProfileReport\n",
116+
"\n",
117+
"df = pd.read_csv('IPL Matches Dataset 2021.csv')\n",
118+
"#df.head()\n",
119+
"#df.shape\n",
120+
"\n",
121+
"df.describe()\n",
122+
"#profile = ProfileReport(df)\n",
123+
"#profile.to_file(output_file=\"covid_19_clean_complete.html\")"
124+
]
125+
},
126+
{
127+
"cell_type": "code",
128+
"execution_count": 2,
129+
"metadata": {},
130+
"outputs": [
131+
{
132+
"name": "stdout",
133+
"output_type": "stream",
134+
"text": [
135+
"<class 'pandas.core.frame.DataFrame'>\n",
136+
"RangeIndex: 21 entries, 0 to 20\n",
137+
"Data columns (total 17 columns):\n",
138+
" # Column Non-Null Count Dtype \n",
139+
"--- ------ -------------- ----- \n",
140+
" 0 id 21 non-null int64 \n",
141+
" 1 city 21 non-null object \n",
142+
" 2 date 21 non-null object \n",
143+
" 3 player_of_match 21 non-null object \n",
144+
" 4 venue 21 non-null object \n",
145+
" 5 neutral_venue 21 non-null int64 \n",
146+
" 6 team1 21 non-null object \n",
147+
" 7 team2 21 non-null object \n",
148+
" 8 toss_winner 21 non-null object \n",
149+
" 9 toss_decision 21 non-null object \n",
150+
" 10 winner 21 non-null object \n",
151+
" 11 result 21 non-null object \n",
152+
" 12 result_margin 20 non-null float64\n",
153+
" 13 eliminator 21 non-null object \n",
154+
" 14 method 0 non-null float64\n",
155+
" 15 umpire1 21 non-null object \n",
156+
" 16 umpire2 21 non-null object \n",
157+
"dtypes: float64(2), int64(2), object(13)\n",
158+
"memory usage: 2.9+ KB\n"
159+
]
160+
}
161+
],
162+
"source": [
163+
"df.info()"
164+
]
165+
},
166+
{
167+
"cell_type": "code",
168+
"execution_count": null,
169+
"metadata": {},
170+
"outputs": [],
171+
"source": []
172+
}
173+
],
174+
"metadata": {
175+
"interpreter": {
176+
"hash": "2e26d2f57d00b66bbacd66603027255515b714fe2db5cd0739a98c8dd623e8a9"
177+
},
178+
"kernelspec": {
179+
"display_name": "Python 3.9.7 64-bit",
180+
"language": "python",
181+
"name": "python3"
182+
},
183+
"language_info": {
184+
"codemirror_mode": {
185+
"name": "ipython",
186+
"version": 3
187+
},
188+
"file_extension": ".py",
189+
"mimetype": "text/x-python",
190+
"name": "python",
191+
"nbconvert_exporter": "python",
192+
"pygments_lexer": "ipython3",
193+
"version": "3.9.7"
194+
},
195+
"orig_nbformat": 4
196+
},
197+
"nbformat": 4,
198+
"nbformat_minor": 2
199+
}

0 commit comments

Comments
 (0)