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docs: docstrings for DataframeAbstract
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* (docs): add docstrings for proxy-methods in `DataframeAbstract` class
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nautics889 committed Sep 10, 2023
1 parent 58be64b commit 4ad7296
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144 changes: 144 additions & 0 deletions pandasai/smart_dataframe/abstract_df.py
Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,9 @@ def columns(self) -> list:
return self.dataframe.columns

def rename(self, columns):
"""
A proxy-call to the dataframe's `.rename()`.
"""
return self.dataframe.rename(columns=columns)

# Index
Expand All @@ -22,143 +25,272 @@ def index(self):
return self.dataframe.index

def set_index(self, keys):
"""
A proxy-call to the dataframe's `.set_index()`.
"""
return self.dataframe.set_index(keys=keys)

def reset_index(self, drop=False):
"""
A proxy-call to the dataframe's `.reset_index()`.
"""
return self.dataframe.reset_index(drop=drop)

# Data
def head(self, n):
"""
A proxy-call to the dataframe's `.head()`.
"""
return self.dataframe.head(n=n)

def tail(self, n):
"""
A proxy-call to the dataframe's `.tail()`.
"""
return self.dataframe.tail(n=n)

def sample(self, n):
"""
A proxy-call to the dataframe's `.sample()`.
"""
return self.dataframe.sample(n=n)

def describe(self):
"""
A proxy-call to the dataframe's `.describe()`.
"""
return self.dataframe.describe()

# Missing data
def isna(self):
"""
A proxy-call to the dataframe's `.isna()`.
"""
return self.dataframe.isna()

def notna(self):
"""
A proxy-call to the dataframe's `.notna()`.
"""
return self.dataframe.notna()

def dropna(self, axis):
"""
A proxy-call to the dataframe's `.dropna()`.
"""
return self.dataframe.dropna(axis=axis)

def fillna(self, value):
"""
A proxy-call to the dataframe's `.fillna()`.
"""
return self.dataframe.fillna(value=value)

# Duplicates
def duplicated(self):
"""
A proxy-call to the dataframe's `.duplicated()`.
"""
return self.dataframe.duplicated()

def drop_duplicates(self, subset):
"""
A proxy-call to the dataframe's `.drop_duplicates()`.
"""
return self.dataframe.drop_duplicates(subset=subset)

# Transform
def apply(self, func):
"""
A proxy-call to the dataframe's `.apply()`.
"""
return self.dataframe.apply(func=func)

def applymap(self, func):
"""
A proxy-call to the dataframe's `.applymap()`.
"""
return self.dataframe.applymap(func=func)

def pipe(self, func):
"""
A proxy-call to the dataframe's `.pipe()`.
"""
return self.dataframe.pipe(func=func)

# Groupby
def groupby(self, by):
"""
A proxy-call to the dataframe's `.groupby()`.
"""
return self.dataframe.groupby(by=by)

def pivot(self, index, columns, values):
"""
A proxy-call to the dataframe's `.pivot()`.
"""
return self.dataframe.pivot(index=index, columns=columns, values=values)

def unstack(self):
"""
A proxy-call to the dataframe's `.unstack()`.
"""
return self.dataframe.unstack()

# Join/Merge
def append(self, other):
"""
A proxy-call to the dataframe's `.append()`.
"""
return self.dataframe.append(other=other)

def join(self, other):
"""
A proxy-call to the dataframe's `.join()`.
"""
return self.dataframe.join(other=other)

def merge(self, other):
"""
A proxy-call to the dataframe's `.merge()`.
"""
return self.dataframe.merge(other=other)

# Combine
def concat(self, others):
"""
A proxy-call to the dataframe's `.concat()`.
"""
return self.dataframe.concat(others=others)

# Statistical
def count(self):
"""
A proxy-call to the dataframe's `.count()`.
"""
return self.dataframe.count()

def mean(self):
"""
A proxy-call to the dataframe's `.mean()`.
"""
return self.dataframe.mean()

def median(self):
"""
A proxy-call to the dataframe's `.median()`.
"""
return self.dataframe.median()

def std(self):
"""
A proxy-call to the dataframe's `.std()`.
"""
return self.dataframe.std()

def min(self):
"""
A proxy-call to the dataframe's `.min()`.
"""
return self.dataframe.min()

def max(self):
"""
A proxy-call to the dataframe's `.max()`.
"""
return self.dataframe.max()

def abs(self):
"""
A proxy-call to the dataframe's `.abs()`.
"""
return self.dataframe.abs()

def prod(self):
"""
A proxy-call to the dataframe's `.prod()`.
"""
return self.dataframe.prod()

def sum(self):
"""
A proxy-call to the dataframe's `.sum()`.
"""
return self.dataframe.sum()

def nunique(self):
"""
A proxy-call to the dataframe's `.nunique()`.
"""
return self.dataframe.nunique()

def value_counts(self):
"""
A proxy-call to the dataframe's `.value_counts()`.
"""
return self.dataframe.value_counts()

def corr(self):
"""
A proxy-call to the dataframe's `.corr()`.
"""
return self.dataframe.corr()

def cov(self):
"""
A proxy-call to the dataframe's `.cov()`.
"""
return self.dataframe.cov()

# Window
def rolling(self, window):
"""
A proxy-call to the dataframe's `.window()`.
"""
return self.dataframe.rolling(window=window)

def expanding(self, min_periods):
"""
A proxy-call to the dataframe's `.expanding()`.
"""
return self.dataframe.expanding(min_periods=min_periods)

def resample(self, rule):
"""
A proxy-call to the dataframe's `.resample()`.
"""
return self.dataframe.resample(rule=rule)

# Plotting
def plot(self):
"""
A proxy-call to the dataframe's `.plot()`.
"""
return self.dataframe.plot()

def hist(self):
"""
A proxy-call to the dataframe's `.hist()`.
"""
return self.dataframe.hist()

# Exporting
def to_csv(self, path):
"""
A proxy-call to the dataframe's `.to_csv()`.
"""
return self.dataframe.to_csv(path=path)

def to_json(self, path):
"""
A proxy-call to the dataframe's `.to_json()`.
"""
return self.dataframe.to_json(path=path)

def to_sql(self, name, con):
"""
A proxy-call to the dataframe's `.to_sql()`.
"""
return self.dataframe.to_sql(name=name, con=con)

def to_dict(self, orient="dict", into=dict, as_series=True):
Expand All @@ -175,14 +307,26 @@ def to_dict(self, orient="dict", into=dict, as_series=True):
)

def to_numpy(self):
"""
A proxy-call to the dataframe's `.to_numpy()`.
"""
return self.dataframe.to_numpy()

def to_markdown(self):
"""
A proxy-call to the dataframe's `.to_markdown()`.
"""
return self.dataframe.to_markdown()

# Query
def query(self, expr):
"""
A proxy-call to the dataframe's `.query()`.
"""
return self.dataframe.query(expr=expr)

def filter(self, expr):
"""
A proxy-call to the dataframe's `.filter()`.
"""
return self.dataframe.filter(items=expr)

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