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Left align pandas comparison tables
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tk3369 committed Sep 12, 2020
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Expand Up @@ -34,7 +34,7 @@ as row indices rather than a separate `id` column.
### Accessing data

| Operation | pandas | DataFrames.jl |
|----------------------------|------------------------|------------------------------------|
|:---------------------------|:-----------------------|:-----------------------------------|
| Cell indexing by location | `df.iloc[1, 1]` | `df[2, 2]` |
| Row slicing by location | `df.iloc[1:3]` | `df[2:3, :]` |
| Column slicing by location | `df.iloc[:, 1:]` | `df[:, 2:end]` |
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### Common operations

| Operation | pandas | DataFrames.jl |
|--------------------------|----------------------------------------------------------------|---------------------------------------------|
|:-------------------------|:---------------------------------------------------------------|:--------------------------------------------|
| Reduce multiple values | `df['z'].mean(skipna = False)` | `mean(df.z)` |
| | `df['z'].mean()` | `mean(skipmissing(df.z))` |
| | `df[['z']].agg(['mean'])` | `combine(df, :z => mean ∘ skipmissing)` |
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The following table illustrates some common grouping and aggregation usages.

| Operation | pandas | DataFrames.jl |
|---------------------------------|---------------------------------------------------------------------------------------|------------------------------------------------------|
|:--------------------------------|:--------------------------------------------------------------------------------------|:-----------------------------------------------------|
| Aggregate by groups | `df.groupby('grp')['x'].mean()` | `combine(groupby(df, :grp), :x => mean)` |
| Rename column after aggregation | `df.groupby('grp')['x'].mean().rename("my_mean")` | `combine(groupby(df, :grp), :x => mean => :my_mean)` |
| Add aggregated data as column | `df.join(df.groupby('grp')['x'].mean(), on='grp', rsuffix='_mean')` | `transform(groupby(df, :grp), :x => mean)` |
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This section includes more complex examples.

| Operation | pandas | DataFrames.jl |
|----------------------------------------|------------------------------------------------------------------------------|-----------------------------------------------------------|
|:---------------------------------------|:-----------------------------------------------------------------------------|:----------------------------------------------------------|
| Complex Function | `df[['z']].agg(lambda v: np.mean(np.cos(v)))` | `combine(df, :z => v -> mean(cos, skipmissing(v)))` |
| Aggregate multiple columns | `df.agg({'x': max, 'y': min})` | `combine(df, :x => maximum, :y => minimum)` |
| | `df[['x','y']].mean()` | `combine(df, [:x, :y] .=> mean)` |
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