saadkhan_khi_python_assignment.ipynb

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     "text": [
      "Q1: Load the dataset to pandas dataframe and print names of columns\n",
      "\n",
      "\n",
      "Index(['age', 'bp', 'sg', 'al', 'su', 'rbc', 'pc', 'pcc', 'ba', 'bgr', 'bu',\n",
      "       'sc', 'sod', 'pot', 'hemo', 'pcv', 'wbcc', 'rbcc', 'htn', 'dm', 'cad',\n",
      "       'appet', 'pe', 'ane', 'class'],\n",
      "      dtype='object')\n",
      "\n",
      "\n",
      "\n",
      "Q2: Display first 5 rows in the dataset.\n",
      "\n",
      "\n",
      "   age   bp     sg   al   su     rbc        pc         pcc          ba  bgr  \\\n",
      "0  NaN  NaN    NaN  NaN  NaN     NaN       NaN         NaN         NaN  NaN   \n",
      "1   48   80  1.020    1    0       ?    normal  notpresent  notpresent  121   \n",
      "2    7   50  1.020    4    0       ?    normal  notpresent  notpresent    ?   \n",
      "3   62   80  1.010    2    3  normal    normal  notpresent  notpresent  423   \n",
      "4   48   70  1.005    4    0  normal  abnormal     present  notpresent  117   \n",
      "\n",
      "   ...   pcv  wbcc rbcc  htn   dm  cad appet   pe  ane class  \n",
      "0  ...   NaN   NaN  NaN  NaN  NaN  NaN   NaN  NaN  NaN   NaN  \n",
      "1  ...    44  7800  5.2  yes  yes   no  good   no   no   ckd  \n",
      "2  ...    38  6000    ?   no   no   no  good   no   no   ckd  \n",
      "3  ...    31  7500    ?   no  yes   no  poor   no  yes   ckd  \n",
      "4  ...    32  6700  3.9  yes   no   no  poor  yes  yes   ckd  \n",
      "\n",
      "[5 rows x 25 columns]\n",
      "\n",
      "\n",
      "\n",
      "Q3: Check if dataset is in cleaned form else clean it. Check Diabetes Mellitus(dm) variable and print what type of values it has.\n",
      "\n",
      "\n",
      "[nan 'yes' 'no' ' yes' '\\tno' '\\tyes' '?']\n",
      "\n",
      "\n",
      "\n",
      "Q4: The dataset is not in clean form. Write a function that takes pandas dataframe as an input, remove these characters i-e ( '\t', ' ') from the string value and replace with 'nan' if the string value has only unicode characters i-e ('?'). The function should apply this transformation to all columns in dataframe and for cross check display unique values of Diabetes Mellitus(dm).\n",
      "\n",
      "\n",
      "[nan 'yes' 'no']\n",
      "\n",
      "\n",
      "\n",
      "Q5: Change datatype to Numerical of following columns in Dataframe. columns 'age', 'bp', 'bgr', 'bu', 'sc', 'sod', 'pot', 'hemo', 'pcv', 'wbcc', 'rbcc'\n",
      "\n",
      "\n",
      "Type changed.\n",
      "\n",
      "\n",
      "Q6: Count the number of normal or abnormal red blood cells people having Chronic Kidney Disease(CKD).\n",
      "\n",
      "\n",
      "Abnormal\n",
      "47\n",
      "Normal\n",
      "60\n"
     ]
    },
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     "text": [
      "\n",
      "\n",
      "\n",
      "Q7: Display maximum blood pressure having Chronic Kidney Disease(CKD).\n",
      "\n",
      "\n",
      "180.0\n",
      "\n",
      "\n",
      "\n",
      "Q8: Create a csv file of cleaned data in dataframe with name 'clean_chronic_kidney_disease.csv'\n",
      "\n",
      "\n",
      "File successfully created\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def clean_dataframe(df):\n",
    "    func = lambda x: str(x).strip()\n",
    "    df=df.applymap(func)    \n",
    "    df=df.replace(\"?\",float('nan'))\n",
    "    df=df.replace(\"nan\",float('nan'))\n",
    "    return df\n",
    "def print_unique_values(df):\n",
    "    size=len(df.columns)\n",
    "    for x in range(0,size):\n",
    "        print(str(df.columns[x])+\" \"+str(df.iloc[:,x].unique()))\n",
    "\n",
    "\n",
    "#Q1\n",
    "os.chdir(\"C:/Users/Saad.Khan/Documents\")\n",
    "dataset=pd.read_csv(\"Assignment Material/Assignment Material/Dataset/chronic_kidney_disease_updated.csv\")\n",
    "#print_unique_values(dataset)\n",
    "print(\"Q1: Load the dataset to pandas dataframe and print names of columns\\n\\n\")\n",
    "print(dataset.columns)\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "\n",
    "#Q2\n",
    "print(\"Q2: Display first 5 rows in the dataset.\\n\\n\")\n",
    "print(dataset.loc[0:4,:])\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "#Q3\n",
    "print(\"Q3: Check if dataset is in cleaned form else clean it. Check Diabetes Mellitus(dm) variable and print what type of values it has.\\n\\n\")\n",
    "print(dataset.dm.unique())\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "#Q4\n",
    "dataset=clean_dataframe(dataset)\n",
    "print(\"Q4: The dataset is not in clean form. Write a function that takes pandas dataframe as an input, remove these characters i-e ( '\\t', ' ') from the string value and replace with 'nan' if the string value has only unicode characters i-e ('?'). The function should apply this transformation to all columns in dataframe and for cross check display unique values of Diabetes Mellitus(dm).\\n\\n\")\n",
    "print(dataset.dm.unique())\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "#Q5\n",
    "print(\"Q5: Change datatype to Numerical of following columns in Dataframe. columns 'age', 'bp', 'bgr', 'bu', 'sc', 'sod', 'pot', 'hemo', 'pcv', 'wbcc', 'rbcc'\\n\\n\")\n",
    "\n",
    "dataset[['age', 'bp', 'bgr', 'bu', 'sc', 'sod', 'pot', 'hemo', 'pcv', 'wbcc', 'rbcc']]=dataset[['age', 'bp', 'bgr', 'bu', 'sc', 'sod', 'pot', 'hemo', 'pcv', 'wbcc', 'rbcc']].astype(float)\n",
    "print(\"Type changed.\\n\\n\")\n",
    "\n",
    "#Q6\n",
    "print(\"Q6: Count the number of normal or abnormal red blood cells people having Chronic Kidney Disease(CKD).\\n\\n\")\n",
    "print(\"Abnormal\")\n",
    "print(dataset.loc[(dataset[\"rbc\"] == \"abnormal\") & (dataset[\"class\"] == \"ckd\"),\"rbc\"].count())\n",
    "print(\"Normal\")\n",
    "print(dataset.loc[(dataset[\"rbc\"] == \"normal\") & (dataset[\"class\"] == \"ckd\"),\"rbc\"].count())\n",
    "dataset[dataset[\"class\"]==\"ckd\"].rbc.value_counts().plot(kind='bar')\n",
    "plt.show()\n",
    "\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "#Q7\n",
    "print(\"Q7: Display maximum blood pressure having Chronic Kidney Disease(CKD).\\n\\n\")\n",
    "print(dataset.loc[:,\"bp\"].max())\n",
    "print(\"\\n\\n\")\n",
    "\n",
    "#Q8\n",
    "print(\"Q8: Create a csv file of cleaned data in dataframe with name 'clean_chronic_kidney_disease.csv'\\n\\n\")\n",
    "dataset.to_csv(\"clean_chronic_kidney_disease.csv\", sep=',', encoding='utf-8',index=False)\n",
    "clean_dataset=pd.read_csv(\"clean_chronic_kidney_disease.csv\")\n",
    "#print_unique_values(clean_dataset)\n",
    "print(\"File successfully created\\n\\n\")"
   ]
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