<jupyter_start><jupyter_text>Pandas<jupyter_code>df = pd.read_csv("Current_Employee_Names__Salaries__and_Position_Titles.csv")
df
# column
df.Department
df["Department"]
df.columns  # available columns
df.index  # index, default Range Index start from 0
df.iloc[16596]  # row
df.iloc[16596, 0]  # cell
df[df.Name.str.contains("LIGHTFOOT")]  # filter column Name with str containing LIGHTFOOT
df.Department.unique()
df.Department.value_counts()
df.Department.value_counts(normalize=True) * 100
out = (
    df[
        ~df["Annual Salary"].isnull()
    ]
    .groupby(df.Department)[["Annual Salary"]]
    .mean()
    .sort_values("Annual Salary", ascending=False)
)
out.head()
df.sort_values("Annual Salary", ascending=False).head(20)<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '114390', 'license': 'MIT', 'n_tokens_mistral': 300, 'n_tokens_neox': 277, 'n_words': 48, 'path': '06_pandas.ipynb', 'repo_name': 'AnkurDedania/pythonTraining', 'size': '763'}