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nmd2k

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testcm

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[ "heading element with class = \"heading\"", "heading element with id = \"heading\"", "heading element with name = \"heading\"", "heading element with slector= \"heading\"" ]

[ "Selector", "Element", "Fade effect", "Radio button" ]

[ "jQuery.getScript( url, [callback] )", "jQuery.post( url, [data], [callback], [type] )", "jQuery.post( url, [type] )", "jQuery.getJSON( url, [data], [callback] )" ]

[ "jQuery.each() Method", "jQuery.conflict() Method", "jQuery.noConflict() Method", "jQuery.parseJSON() Method" ]

[ "jQuery()", "$()", "script()", "Both jQuery() and $()" ]

[ "fadeIn()", "fadeOut()", "toggle()", "D) fadeToggle()" ]

[ "Using args. length Property", "Using arguments.length Property", "Both of the above", "None of the above" ]

[ "Modal", "Version", "Browser", "Navigator" ]

[ "toggleClass()", "switch()", "altClass()", "switchClass()" ]

[ "GetCharAt()", "CharAt()", "CharacterAt()", "None Of The Above" ]

[ "jQuery(function)", "$(function)", "#(function)", "read(function)" ]

[ "$(:password)", "$(\":text\")", "$(\":password\")", "$(:text)" ]

[ "css()", "Scss()", "html()", "style()" ]

[ "$(\"h1\").html(\"background-color\",\"Green\");", "$(\"h1\").layout(\"background-color\",\"Green\");", "$(\"h1\").style(\"background-color\",\"Green\");", "$(\"h1\").css(\"background-color\",\"Green\");" ]

[ "getIs( selector )", "findls( selector )", "is( selector )", "None of the above." ]

[ "attach(type, [data], fn )", "catch(type, [data], fn )", "bind( type, [data], fn )", "All of the above" ]

[ "jQuery check() Method", "jQuery extend() Method", "jQuery obj() Method", "None of the above" ]

[ "@ sign", "% sign", "& sign", "$ sign" ]

[ "AJAX", "Animating", "Chaining", "Event bubbling" ]

[ "path.parse()", "path.Reset()", "path.countReset()", "parse.countReset()" ]

[ "Buffer.copy()", "Buffer.include()", "Buffer.copy()", "Buffer.equals()" ]

[ "console.timeEnd()", "console.timeStamp()", "console.trace()", "console.end()" ]

[ "cipher.last()", "cipher.start()", "cipher.final()", "cipher.update()" ]

[ "crypto.incrypt()", "cipher.update()", "cipher.increment()", "crypto.scrypt()" ]

[ "Buffer", "Timer", "Speed", "Console" ]

[ "Assert", "Http", "DNS", "Lookup" ]

[ "url.encode", "url.decrypt", "url.encrypt", "url.hash" ]

[ "Open SSL", "v8", "libuv", "Zlib" ]

[ "path.relative()", "path.parse()", "path.absolute()", "path.imaginary()" ]

[ "socket.send()", "socket.get()", "socket.post()", "socket.ref()" ]

[ "npm install -g nodemon", "node install -g nodemon", "node install node", "node install -l nodemon" ]

[ "Single Page", "JSON APIs based", "CPU intensive", "Data-Intensive" ]

[ "It is present in the root directory of any Node application.", "It is used to define the properties of a package.", "It is used to update the dependencies of an application.", "All of the above." ]

[ "fs.open(path, flags[, mode], callback)", "fs.stat(path, callback)", "fs.readFile(path, flags[, mode], callback)", "None of the above" ]

[ "Utility", "URL", "UDP", "Process" ]

[ "util.format()", "util.inherits()", "util.callbackify()", "util.debuglog()" ]

[ "dnsPromises.resolve4()", "dnsPromises.resolveAny()", "dnsPromises.resolveMx()", "dnsPromises.getServers()" ]

[ "dns.resolveNaptr()", "dns.resolve6()", "dns.resolvePtr()", "dns.resolve4()" ]

[ "Process", "Stream", "Path", "Buffers" ]

[ "http.server.setTimeout()", "http.server.timeout()", "http.server.close()", "http.server.headersTimeout()" ]

[ "zlib.createDeflate()", "zlib.createGunzip()", "zlib.createUnzip()", "zlib.createZip()" ]

[ "cwd();", "cmd();", "pwd();", "None of the above" ]

[ "Global", "Local", "Global Function", "Local to object" ]

[ "path.get()", "path.set()", "path.format()", "path.return()" ]

[ "Jade", "Vash", "Handlebars", "All of the above" ]

[ "fs.delete(fd, len, callback)", "fs.remove(fd, len, callback)", "fs.ftruncate(fd, len, callback)", "None of the above." ]

[ "npm ls -g", "npm ls", "node ls -g", "node ls" ]

[ "zlib", "HTTPS", "dgram", "fsread" ]

[ "Expose", "Module", "Exports", "All of the above" ]

[ "JavaScript", "C", "C++", "All of the above" ]

[ "v8.Serializer.writeValue()", "v8.Serializer.writeHeader()", "v8.serialize()", "v8.deserialize()" ]

[ "zlib.constants()", "zlib.createBrotliDecompress()", "zlib.createUnzip()", "zlib.createBrotliCompress()" ]

[ "agent.minFreeSockets", "agent.maxFreeSockets", "agent.maxSockets", "agent.minSockets" ]

[ "stringDecoder.start()", "stringDecoder.end()", "stringEncoder.start()", "stringEncoder.end()" ]

[ "Utility", "Timer", "Decoder", "Stream" ]

[ "Query", "String decoder", "steam", "VM" ]

[ "path.argv()", "path.join()", "path.chdir()", "path.argv()" ]

[ "path.extname()", "path.basename()", "path.dirname()", "path.delimiter" ]

[ "os.freemem()", "os.uptime()", "os.getPriority()", "os.homedir()" ]

[ "os.EOL", "os.endianness()", "os.cpus()", "os.arch()" ]

[ "URL()", "Global()", "Timers()", "Buffers()" ]

[ "Crypto module", "File module", "Os module", "Path module" ]

[ "path.Query()", "path.render()", "path.isAbsolute()", "path.Absolute()" ]

[ "dns.resolveNs()", "dns.resolveNapt()", "dns.resolveMx()", "dns.resolvePtr()" ]

[ "A plotting library", "A machine learning framework", "A scientific computing library", "A web development framework" ]

[ "df.save_csv(\"filename.csv\")", "df.write_csv(\"filename.csv\")", "df.to_csv(\"filename.csv\")", "df.export_csv(\"filename.csv\")" ]

[ "df.resample()", "df.time_resample()", "df.groupby(\"time_column\").resample()", "df.time_groupby().resample()" ]

[ "To melt a DataFrame into a longer format", "To create a melted cheese plot", "To melt a DataFrame into a wider format", "To melt a DataFrame into a binary format" ]

[ "Use df.fillna(value) to replace missing values", "Use df.dropna() to remove rows with missing values", "Both A and B", "Neither A nor B" ]

[ "df.concat()", "df.join()", "df.merge()", "df.combine()" ]

[ "normalized_arr = (arr - arr.min()) / (arr.max() - arr.min())", "normalized_arr = np.scale(arr)", "normalized_arr = arr.normalize()", "normalized_arr = (arr - arr.mean()) / arr.std()" ]

[ "mean_values = np.mean(arr, axis=1)", "mean_values = arr.mean(axis=0)", "mean_values = np.average(arr, axis=1)", "mean_values = arr.mean(axis=2)" ]

[ "intersection = np.intersect(a, b)", "intersection = np.common(a, b)", "intersection = np.intersect1d(a, b)", "intersection = a.intersection(b)" ]

[ "cumulative_product = np.prod(arr)", "cumulative_product = arr.cumprod()", "cumulative_product = np.multiply(arr)", "cumulative_product = np.cumprod(arr)" ]

[ "diagonal_matrix = np.diag(arr)", "diagonal_matrix = np.diagonal(arr)", "diagonal_matrix = np.create_diag(arr)", "diagonal_matrix = arr.diag()" ]

[ "Clips the array values to be within a specified range", "Clips the array to its maximum value", "Clips the array to its minimum value", "Clips the array based on a boolean condition" ]

[ "np.sqrt(arr)", "arr.sqrt()", "np.square_root(arr)", "arr.square_root()" ]

[ "filtered_elements = arr[arr > 10]", "filtered_elements = np.extract(arr, arr > 10)", "filtered_elements = np.filter(arr, arr > 10)", "filtered_elements = arr.extract(arr > 10)" ]

[ "max_index = np.find_max_index(arr)", "max_index = np.argmax(arr)", "max_index = arr.max_index()", "max_index = np.argmax(arr)" ]

[ "Use the df.drop_duplicates() method", "Use the df.remove_duplicates() method", "Use the df.drop_duplicate_rows() method", "Use the df.eliminate_duplicates() method" ]

[ "Creates an array with ones", "Creates an array with random values", "Creates an array with zeros", "Creates an identity matrix" ]

[ "arr[1, 2]", "arr[2, 3]", "arr[1][2]", "arr[2][3]" ]

[ "a * b", "np.multiply(a, b)", "np.mult(a, b)", "a.dot(b)" ]

[ "Creates an array with values from 5 to 15", "Creates an array with values from 5 to 14 with a step of 2", "Creates an array with values from 5 to 15 with a step of 2", "Creates an array with values from 5 to 14" ]

[ "arr.mean()", "np.mean(arr)", "mean(arr)", "arr.average()" ]

[ "Changes the shape of an array", "Transposes the array", "Rotates the array", "Inverts the array" ]

[ "(1, 5)", "(5,)", "(5, 1)", "(1,)" ]

[ "dot_product = a x b", "dot_product = np.dot(a, b)", "dot_product = a.dot(b)", "dot_product = np.cross(a, b)" ]

[ "np.array(list)", "numpy(list)", "array(list)", "create.array(list)" ]

[ "df.resample()", "df.time_resample()", "df.groupby(\"time_column\").resample()", "df.time_groupby().resample()" ]

[ "df.reset_index()", "df.set_index()", "df.index_reset()", "df.index_reset()" ]

[ "The number of non-null values", "The number of unique values", "The number of distinct groups", "The number of unique rows" ]

[ "To melt a DataFrame into a longer format", "To create a melted cheese plot", "To melt a DataFrame into a wider format", "To melt a DataFrame into a binary format" ]

[ "Use the df.drop_duplicates() method", "Use the df.remove_duplicates() method", "Use the df.drop_duplicate_rows() method", "Use the df.eliminate_duplicates() method" ]

[ "To display the last few rows of a DataFrame", "To display the first few rows of a DataFrame", "To display summary statistics of a DataFrame", "To display summary statistics of a DataFrame" ]

[ "Use df.fillna(value) to replace missing values", "Use df.dropna() to remove rows with missing values", "Both A and B", "Neither A nor B" ]

[ "df.save_csv(\"filename.csv\")", "df.write_csv(\"filename.csv\")", "df.to_csv(\"filename.csv\")", "df.export_csv(\"filename.csv\")" ]

[ "Returns the smallest values in a DataFrame", "Returns the largest values in a DataFrame", "Returns the smallest values in a column", "Returns the largest values in a column" ]

[ "To cut a DataFrame into smaller pieces", "To categorize continuous data into discrete bins", "To remove duplicate values from a DataFrame", "To concatenate DataFrames along a particular axis" ]

[ "df.filter(condition)", "df.select_rows(condition)", "df[condition]", "df.filter_rows(condition)" ]