| Preface |
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xi | |
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Part I Introduction to Python |
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3 | (16) |
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Excel Is a Programming Language |
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4 | (8) |
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5 | (1) |
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Programming Best Practices |
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6 | (5) |
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11 | (1) |
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12 | (5) |
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Readability and Maintainability |
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13 | (1) |
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Standard Library and Package Manager |
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14 | (1) |
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15 | (1) |
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16 | (1) |
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Cross-Platform Compatibility |
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17 | (1) |
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17 | (2) |
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2 Development Environment |
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19 | (24) |
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The Anaconda Python Distribution |
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20 | (7) |
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20 | (1) |
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21 | (3) |
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Python REPL: An Interactive Python Session |
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24 | (1) |
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Package Managers: Conda and pip |
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25 | (2) |
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27 | (1) |
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27 | (7) |
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Running Jupyter Notebooks |
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28 | (1) |
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29 | (2) |
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31 | (1) |
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32 | (1) |
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Shutting Down Jupyter Notebooks |
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33 | (1) |
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34 | (7) |
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Installation and Configuration |
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36 | (1) |
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37 | (4) |
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41 | (2) |
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3 Getting Started with Python |
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43 | (34) |
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43 | (7) |
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44 | (1) |
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45 | (2) |
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47 | (2) |
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49 | (1) |
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50 | (2) |
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51 | (1) |
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52 | (1) |
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52 | (6) |
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53 | (2) |
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55 | (2) |
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57 | (1) |
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57 | (1) |
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58 | (6) |
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Code Blocks and the pass Statement |
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58 | (1) |
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The if Statement and Conditional Expressions |
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59 | (1) |
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60 | (3) |
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List, Dictionary, and Set Comprehensions |
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63 | (1) |
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64 | (6) |
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65 | (1) |
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Modules and the import Statement |
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66 | (3) |
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69 | (1) |
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PEP 8: Style Guide for Python Code |
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70 | (4) |
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73 | (1) |
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73 | (1) |
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74 | (3) |
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Part II Introduction to pandas |
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77 | (8) |
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Getting Started with NumPy |
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77 | (4) |
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77 | (2) |
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Vectorization and Broadcasting |
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79 | (1) |
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Universal Functions (ufunc) |
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80 | (1) |
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Creating and Manipulating Arrays |
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81 | (3) |
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Getting and Setting Array Elements |
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82 | (1) |
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Useful Array Constructors |
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83 | (1) |
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83 | (1) |
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84 | (1) |
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5 Data Analysis with pandas |
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85 | (40) |
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85 | (6) |
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88 | (2) |
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90 | (1) |
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91 | (16) |
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92 | (5) |
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97 | (3) |
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100 | (2) |
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102 | (1) |
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103 | (2) |
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Working with Text Columns |
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105 | (1) |
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105 | (2) |
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107 | (1) |
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107 | (4) |
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108 | (1) |
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109 | (2) |
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Descriptive Statistics and Data Aggregation |
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111 | (4) |
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111 | (1) |
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112 | (1) |
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113 | (2) |
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115 | (4) |
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115 | (2) |
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117 | (2) |
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Importing and Exporting DataFrames |
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119 | (4) |
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120 | (1) |
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121 | (2) |
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123 | (2) |
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6 Time Series Analysis with pandas |
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125 | (18) |
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126 | (5) |
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Creating a Datetime Index |
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126 | (2) |
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Filtering a Datetime Index |
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128 | (1) |
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129 | (2) |
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Common Time Series Manipulations |
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131 | (7) |
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Shifting and Percentage Changes |
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131 | (2) |
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133 | (3) |
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136 | (1) |
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137 | (1) |
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138 | (1) |
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139 | (4) |
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Part III Reading and Writing Excel Files Without Excel |
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7 Excel File Manipulation with pandas |
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143 | (12) |
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Case Study: Excel Reporting |
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143 | (4) |
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Reading and Writing Excel Files with pandas |
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147 | (7) |
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The read_excel Function and ExcelFile Class |
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147 | (5) |
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The to_excel Method and ExcelWriter Class |
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152 | (2) |
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Limitations When Using pandas with Excel Files |
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154 | (1) |
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154 | (1) |
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8 Excel File Manipulation with Reader and Writer Packages |
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155 | (28) |
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The Reader and Writer Packages |
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155 | (14) |
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When to Use Which Package |
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156 | (1) |
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157 | (2) |
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159 | (4) |
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163 | (2) |
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165 | (1) |
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166 | (3) |
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Advanced Reader and Writer Topics |
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169 | (10) |
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Working with Big Excel Files |
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169 | (4) |
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Formatting DataFrames in Excel |
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173 | (5) |
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Case Study (Revisited): Excel Reporting |
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178 | (1) |
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179 | (4) |
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Part IV Programming the Excel Application with xlwings |
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183 | (26) |
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Getting Started with xlwings |
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184 | (10) |
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Using Excel as Data Viewer |
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184 | (2) |
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186 | (7) |
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193 | (1) |
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Converters, Options, and Collections |
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194 | (10) |
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195 | (1) |
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196 | (2) |
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Charts, Pictures, and Defined Names |
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198 | (4) |
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Case Study (Re-Revisited): Excel Reporting |
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202 | (2) |
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204 | (4) |
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204 | (2) |
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206 | (1) |
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How to Work Around Missing Functionality |
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207 | (1) |
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208 | (1) |
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10 Python-Powered Excel Tools |
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209 | (14) |
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Using Excel as Frontend with xlwings |
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209 | (9) |
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210 | (2) |
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212 | (1) |
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212 | (1) |
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213 | (5) |
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218 | (4) |
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218 | (1) |
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Standalone Workbooks: Getting Rid of the xlwings Add-in |
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219 | (1) |
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220 | (1) |
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221 | (1) |
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222 | (1) |
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11 The Python Package Tracker |
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223 | (28) |
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223 | (3) |
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226 | (14) |
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226 | (3) |
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229 | (9) |
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238 | (2) |
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240 | (10) |
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241 | (4) |
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245 | (3) |
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248 | (2) |
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250 | (1) |
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12 User-Defined Functions (UDFs) |
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251 | (30) |
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Getting Started with UDFs |
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252 | (5) |
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252 | (5) |
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Case Study: Google Trends |
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257 | (14) |
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Introduction to Google Trends |
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257 | (1) |
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Working with DataFrames and Dynamic Arrays |
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258 | (5) |
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Fetching Data from Google Trends |
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263 | (4) |
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267 | (2) |
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269 | (2) |
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271 | (6) |
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Basic Performance Optimization |
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272 | (2) |
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274 | (2) |
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276 | (1) |
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277 | (4) |
| A Conda Environments |
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281 | (4) |
| B Advanced VS Code Functionality |
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285 | (6) |
| C Advanced Python Concepts |
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291 | (8) |
| Index |
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299 | |
Lisainfo e-raamatute kohta