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[`TS.CREATE`](https://oss.redis.com/redistimeseries/commands/#tscreate) command creates a new time series.\n\nHere, we'll create a new time series \"`temperature`\":\n\n```javascript\n\nimport { createClient } from 'redis';\nimport { TimeSeriesDuplicatePolicies, TimeSeriesEncoding, TimeSeriesAggregationType } from '@redis/time-series';\n\n...\nconst created = await client.ts.create('temperature', {\n  RETENTION: 86400000, // 1 day in milliseconds\n  ENCODING: TimeSeriesEncoding.UNCOMPRESSED, // No compression - When not specified, the option is set to COMPRESSED\n  DUPLICATE_POLICY: TimeSeriesDuplicatePolicies.BLOCK, // No duplicates - When not specified: set to the global DUPLICATE_POLICY configuration of the database (which by default, is BLOCK).\n});\n\nif (created === 'OK') {\n  console.log('Created timeseries.');\n} else {\n  console.log('Error creating timeseries :(');\n  process.exit(1);\n}\n```\n\n### Adding new value to a Time Series data structure in Redis\n\nWith RedisTimeSeries, we can add a single value to time series data structure using the [`TS.ADD`](https://redis.io/commands/ts.add/) command and if we would like to add multiple values we can use the [`TS.MADD`](https://redis.io/commands/ts.madd/) command.\n\n```javascript\n\nlet value = Math.floor(Math.random() * 1000) + 1; // Random data point value\nlet currentTimestamp = 1640995200000; // Jan 1 2022 00:00:00\nlet num = 0;\n\nwhile (num < 10000) {\n  // Add a new value to the timeseries, providing our own timestamp:\n  // https://redis.io/commands/ts.add/\n  await client.ts.add('temperature', currentTimestamp, value);\n  console.log(`Added timestamp ${currentTimestamp}, value ${value}.`);\n\n  num += 1;\n  value = Math.floor(Math.random() * 1000) + 1; // Get another random value\n  currentTimestamp += 1000; // Move on one second.\n}\n\n// Add multiple values to the timeseries in round trip to the server:\n// https://redis.io/commands/ts.madd/\nconst response = await client.ts.mAdd([{\n  key: 'temperature',\n  timestamp: currentTimestamp + 60000,\n  value: Math.floor(Math.random() * 1000) + 1\n}, {\n  key: 'temperature',\n  timestamp: currentTimestamp + 120000,\n  value: Math.floor(Math.random() * 1000) + 1\n}]);\n```\n\n### Retrieving Time Series data from Redis\n\nWith RedisTimeSeries, we can retrieve the time series data using the [`TS.RANGE`](https://redis.io/commands/ts.range/) command by passing the criteria as follows:\n\n```javascript\n// Query the timeseries with TS.RANGE:\n// https://redis.io/commands/ts.range/\nconst fromTimestamp = 1640995200000; // Jan 1 2022 00:00:00\nconst toTimestamp = 1640995260000; // Jan 1 2022 00:01:00\nconst rangeResponse = await client.ts.range('temperature', fromTimestamp, toTimestamp, {\n  // Group into 10 second averages.\n  AGGREGATION: {\n    type: TimeSeriesAggregationType.AVERAGE,\n    timeBucket: 10000\n  }\n});\n\nconsole.log('RANGE RESPONSE:');\n// rangeResponse looks like:\n// [\n//   { timestamp: 1640995200000, value: 356.8 },\n//   { timestamp: 1640995210000, value: 534.8 },\n//   { timestamp: 1640995220000, value: 481.3 },\n//   { timestamp: 1640995230000, value: 437 },\n//   { timestamp: 1640995240000, value: 507.3 },\n//   { timestamp: 1640995250000, value: 581.2 },\n//   { timestamp: 1640995260000, value: 600 }\n// ]\n```\n\n### Altering Time Series data Stored in Redis\n\nRedisTimeSeries includes commands that can update values in a time series data structure.\n\nUsing the [`TS.ALTER`](https://redis.io/commands/ts.alter/) command, we can update time series retention like this:\n\n```javascript\n// https://redis.io/commands/ts.alter/\nconst alterResponse = await client.ts.alter('temperature', {\n  RETENTION: 0 // Keep the entries forever\n});\n```\n\n### Retrieving Information about the timeseries Stored in Redis\n\nRedisTimeSeries also includes commands that can help to view the information on the state of a time series.\n\nUsing the [`TS.INFO`](https://redis.io/commands/ts.info/) command, we 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