pip install pandas

Collecting pandas
  Downloading pandas-2.3.0-cp312-cp312-win_amd64.whl.metadata (19 kB)
Requirement already satisfied: numpy>=1.26.0 in c:\users\sanjay\miniconda3\envs\py312\lib\site-packages (from pandas) (2.3.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\sanjay\miniconda3\envs\py312\lib\site-packages (from pandas) (2.9.0.post0)
Requirement already satisfied: pytz>=2020.1 in c:\users\sanjay\miniconda3\envs\py312\lib\site-packages (from pandas) (2025.2)
Requirement already satisfied: tzdata>=2022.7 in c:\users\sanjay\miniconda3\envs\py312\lib\site-packages (from pandas) (2025.2)
Requirement already satisfied: six>=1.5 in c:\users\sanjay\miniconda3\envs\py312\lib\site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)
Downloading pandas-2.3.0-cp312-cp312-win_amd64.whl (11.0 MB)
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Installing collected packages: pandas
Successfully installed pandas-2.3.0
Note: you may need to restart the kernel to use updated packages.

print("testing pynotes 2")

testing pynotes 2

import pandas as pd
data={
    'Name':['sanjay','asha','ravi'],
    'score':[85,90,78]
}
df=pd.DataFrame(data)
print(df)
df_csv=pd.read_csv("students.csv")
print(df_csv)
print()
print(df_csv.head())
print()
print(df_csv.tail())
print()
print(df_csv["Score"])
print()
print(df_csv[["Name","Score"]] )
print()
print(df_csv[df_csv["Score"]>85])
print()
print(df_csv)
print()
df_csv["Passed"]=df_csv["Score"]>=80
print(df_csv)
print()
print(df_csv.groupby("Subject")["Score"].mean())

     Name  score
0  sanjay     85
1    asha     90
2    ravi     78
     Name  Age  Subject  Score
0  Sanjay   18     Math     85
1    Asha   17  Science     90
2    Ravi   18  English     78
3   Meena   17     Math     92
4   Kiran   19  Science     88

     Name  Age  Subject  Score
0  Sanjay   18     Math     85
1    Asha   17  Science     90
2    Ravi   18  English     78
3   Meena   17     Math     92
4   Kiran   19  Science     88

     Name  Age  Subject  Score
0  Sanjay   18     Math     85
1    Asha   17  Science     90
2    Ravi   18  English     78
3   Meena   17     Math     92
4   Kiran   19  Science     88

0    85
1    90
2    78
3    92
4    88
Name: Score, dtype: int64

     Name  Score
0  Sanjay     85
1    Asha     90
2    Ravi     78
3   Meena     92
4   Kiran     88

    Name  Age  Subject  Score
1   Asha   17  Science     90
3  Meena   17     Math     92
4  Kiran   19  Science     88

     Name  Age  Subject  Score
0  Sanjay   18     Math     85
1    Asha   17  Science     90
2    Ravi   18  English     78
3   Meena   17     Math     92
4   Kiran   19  Science     88

     Name  Age  Subject  Score  Passed
0  Sanjay   18     Math     85    True
1    Asha   17  Science     90    True
2    Ravi   18  English     78   False
3   Meena   17     Math     92    True
4   Kiran   19  Science     88    True

Subject
English    78.0
Math       88.5
Science    89.0
Name: Score, dtype: float64