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pandas: select one column?
df['col']
pandas: select multiple columns?
df[['col1', 'col2']]
pandas: filter rows by condition?
df[df['col'] > value]
pandas: filter rows by multiple conditions?
df[(cond1) & (cond2)]
pandas: count categories in a column?
df['col'].value_counts()
pandas: quick statistics for a column?
df['col'].describe()
pandas: mean per group?
df.groupby('col').mean()
pandas: add a column?
df['new'] = values
pandas: sort rows?
df.sort_values('col')
pandas: select by label?
df.loc[row_label, col_name]
pandas: select by position?
df.iloc[row_int, col_int]
AnnData: inspect summary?
print(adata)
AnnData: get shape?
print(adata.shape) → (n_cells, n_genes)
AnnData: access a cell metadata column?
adata.obs['col']
AnnData: get a list of all gene names?
adata.var_names.tolist()
AnnData: subset cells by boolean mask?
adata[mask, :]
AnnData: subset specific genes?
adata[:, ['Hal', 'Vwf']]
AnnData: add cell metadata?
adata.obs['new'] = values
AnnData: access spatial coordinates?
adata.obsm['spatial']
AnnData: save to file?
adata.write_h5ad('out.h5ad')
AnnData: load from file?
ad.read_h5ad('file.h5ad')