SELECT column_name FROM data_frame
df[[‘column_name’]]
SELECT column_name FROM data_frame LIMIT 10
df[[‘column_name’]].head(10)
SELECT * FROM data_frame WHERE column_name = ‘value’
df[(df[‘column_name’] == ‘value’)]
SELECT column_name FROM data_frame WHERE co1_name = ‘value2’ AND col2_name = ‘value2’
df[[‘column_name’]][(df[‘col1_name’] == ‘value1’) & (df[‘col2_name’] == ‘value2’)].head(100)
SELECT date_part, count(*) FROM data_frame GROUP BY date_part – for dataframes with DatetimeIndex
To count column “column_name” by weeks (W)
df.resample(‘W’).agg({“column_name”:’size’})
SELECT date_part, count(*) FROM data_frame WHERE column_name = ‘col_value’ GROUP BY date_part ORDER BY count(*) DESC LIMIT 10 – for dataframes with DatetimeIndex
To count column “column_name” by minutes (1T)
df[(df[‘column_name’] == ‘col_value’)].resample(‘1T’).agg({“column_name”:’size’}).sort_values(by=’column_name’, ascending=False).head(10)
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