pulsar.ipynb

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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 17898 entries, 0 to 17897\n",
            "Data columns (total 9 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   MIP     17898 non-null  float64\n",
            " 1   STDIP   17898 non-null  float64\n",
            " 2   EKIP    17898 non-null  float64\n",
            " 3   SIP     17898 non-null  float64\n",
            " 4   MC      17898 non-null  float64\n",
            " 5   STDC    17898 non-null  float64\n",
            " 6   EKC     17898 non-null  float64\n",
            " 7   SC      17898 non-null  float64\n",
            " 8   TG      17898 non-null  int64  \n",
            "dtypes: float64(8), int64(1)\n",
            "memory usage: 1.2 MB\n"
          ]
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      ],
      "source": [
        "import pandas as pd\n",
        "data = pd.read_csv('/content/asset-v1_ITMOUniversity+DATSC+summer_2022_1+type@asset+block@pulsar_stars_new.csv')\n",
        "data.info()"
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        "data.head()"
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              "          MIP      STDIP      EKIP       SIP        MC       STDC        EKC  \\\n",
              "0  140.562500  55.683782 -0.234571 -0.699648  3.199833  19.110426   7.975532   \n",
              "1  102.507812  58.882430  0.465318 -0.515088  1.677258  14.860146  10.576487   \n",
              "2  103.015625  39.341649  0.323328  1.051164  3.121237  21.744669   7.735822   \n",
              "3  136.750000  57.178449 -0.068415 -0.636238  3.642977  20.959280   6.896499   \n",
              "4   88.726562  40.672225  0.600866  1.123492  1.178930  11.468720  14.269573   \n",
              "\n",
              "           SC  TG  \n",
              "0   74.242225   0  \n",
              "1  127.393580   0  \n",
              "2   63.171909   0  \n",
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      "source": [
        "sample_data = data[((data.TG == 0) & (data.MIP >= 73.4765625) & (data.MIP <= 77.6015625)) | ((data.TG == 1) & (data.MIP >= 25.890625) & (data.MIP <= 31.5078125))]\n",
        "sample_data.info()"
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 203 entries, 61 to 17711\n",
            "Data columns (total 9 columns):\n",
            " #   Column  Non-Null Count  Dtype  \n",
            "---  ------  --------------  -----  \n",
            " 0   MIP     203 non-null    float64\n",
            " 1   STDIP   203 non-null    float64\n",
            " 2   EKIP    203 non-null    float64\n",
            " 3   SIP     203 non-null    float64\n",
            " 4   MC      203 non-null    float64\n",
            " 5   STDC    203 non-null    float64\n",
            " 6   EKC     203 non-null    float64\n",
            " 7   SC      203 non-null    float64\n",
            " 8   TG      203 non-null    int64  \n",
            "dtypes: float64(8), int64(1)\n",
            "memory usage: 15.9 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mean_mip_rounded = round(sample_data['MIP'].mean(), 3)\n",
        "mean_mip_rounded"
      ],
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              "52.159"
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          "execution_count": 12
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