fix conflict

javascriptdata · Aug 15, 2020 · 6d21a47 · 6d21a47
2 parents 7121812 + a2817eb
commit 6d21a47
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diff --git a/README.md b/README.md
@@ -47,6 +47,60 @@ easy and intuitive. It is heavily inspired by [Pandas](https://pandas.pydata.org
   - Robust data preprocessing functions like [OneHotEncoders](https://jsdata.gitbook.io/danfojs/api-reference/general-functions/danfo.onehotencoder), [LabelEncoders](https://jsdata.gitbook.io/danfojs/api-reference/general-functions/danfo.labelencoder), and scalers like [StandardSaler](https://jsdata.gitbook.io/danfojs/api-reference/general-functions/danfo.standardscaler) and [MinMaxScaler](https://jsdata.gitbook.io/danfojs/api-reference/general-functions/danfo.minmaxscaler) are supported on DataFrame and Series
 
 
+
+To use danfo.js via script tags, copy and paste the CDN below to your HTML file
+
+```html
+  <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/index.min.js"></script>
+```
+
+### Example Usage in the Browser
+
+```html
+
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/index.min.js"></script>
+    <title>Document</title>
+</head>
+
+<body>
+
+    <div id="div1"></div>
+    <div id="div2"></div>
+    <div id="div3"></div>
+
+    <script>
+
+        dfd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
+            .then(df => {
+
+                df['AAPL.Open'].plot("div1").box() //makes a box plot
+
+                df.plot("div2").table() //display csv as table
+
+                new_df = df.set_index({ key: "Date" }) //resets the index to Date column
+                new_df.plot("div3").line({ columns: ["AAPL.Open", "AAPL.High"] })  //makes a timeseries plot
+
+            }).catch(err => {
+                console.log(err);
+            })
+
+    </script>
+
+</body>
+
+</html>
+```
+
+Output in Browser:
+
+![](assets/browser-out.gif)
+
+
 ## How to install
 danfo.js is hosted on NPM, and can installed via package managers like npm and yarn
 
@@ -120,59 +174,6 @@ Output in Node Console:
 ![](assets/node-rec.gif)
 
 
-To use danfo.js via script tags, copy and paste the CDN below to your HTML file
-
-```html
-  <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/index.min.js"></script>
-```
-
-### Example Usage in the Browser
-
-```html
-
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/index.min.js"></script>
-    <title>Document</title>
-</head>
-
-<body>
-
-    <div id="div1"></div>
-    <div id="div2"></div>
-    <div id="div3"></div>
-
-    <script>
-
-        dfd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv")
-            .then(df => {
-
-                df['AAPL.Open'].plot("div1").box() //makes a box plot
-
-                df.plot("div2").table() //display csv as table
-
-                new_df = df.set_index({ key: "Date" }) //resets the index to Date column
-                new_df.plot("div3").line({ columns: ["AAPL.Open", "AAPL.High"] })  //makes a timeseries plot
-
-            }).catch(err => {
-                console.log(err);
-            })
-
-    </script>
-
-</body>
-
-</html>
-```
-
-Output in Browser:
-
-![](assets/browser-out.gif)
-
-
 #### [See the Official Getting Started Guide](https://jsdata.gitbook.io/danfojs/getting-started)
 
 ## Documentation

diff --git a/danfojs/src/core/frame.js b/danfojs/src/core/frame.js
@@ -79,36 +79,37 @@ export class DataFrame extends Ndframe {
                 throw Error("No column found. Axis of 1 must be accompanied by an array of column(s) names")
             }
             let self = this;
+            let new_col_data = {}
+            let new_dtype = []
+
             const index = data.map((x) => {
                 let col_idx = self.columns.indexOf(x)
                 if (col_idx == -1) {
                     throw new Error(`column "${x}" does not exist`)
                 }
                 return col_idx
             });
-            const values = this.values
-            let new_dtype = []
-            let new_data = values.map(function (element) {
-                let new_arr = utils.__remove_arr(element, index);
-                new_dtype = utils.__remove_arr(self.dtypes, index);
-                return new_arr;
-            });
+
+            this.col_data.forEach((col, idx) => {
+                if (!index.includes(idx)) {
+                    new_col_data[self.column_names[idx]] = col
+                    new_dtype.push(self.dtypes[idx])
+                }
+            })
 
             if (!kwargs['inplace']) {
-                let old_cols = this.columns
-                let columns = utils.__remove_arr(this.columns, index);
-                let df = new DataFrame(new_data, { columns: columns, index: self.index, dtypes: new_dtype })
-                df.__set_col_property(df, df.col_data, columns, old_cols)
+                let old_cols = self.columns
+                let new_columns = Object.keys(new_col_data)
+                let df = new DataFrame(new_col_data, { index: self.index, dtypes: new_dtype })
+                df.__set_col_property(df, df.col_data, new_columns, old_cols)
                 return df
 
             } else {
-                let new_cols = utils.__remove_arr(this.columns, index);
-                let old_cols = this.columns
-                this.columns = new_cols
-                this.row_data_tensor = tf.tensor(new_data);
-                this.data = new_data
-                this.__set_col_types(new_dtype, false)
-                this.__set_col_property(this, this.col_data, new_cols, old_cols)
+                let old_cols = self.columns
+                let new_columns = Object.keys(new_col_data)
+                this.__update_frame_in_place(null, null, new_col_data, null, new_dtype)
+                this.__set_col_property(self, self.col_data, new_columns, old_cols)
+
             }
 
         } else {
@@ -695,7 +696,8 @@ export class DataFrame extends Ndframe {
         let df = new DataFrame([...this.values],
             {
                 columns: [...this.column_names],
-                index: this.index, dtypes: this.dtypes
+                index: this.index,
+                dtypes: this.dtypes
             })
         return df
     }
@@ -716,7 +718,6 @@ export class DataFrame extends Ndframe {
     }
 
     /**
-    * Generate a new DataFrame with the specified index.
     * Set the DataFrame index (row labels) using an array of the same length.
     * @param {kwargs} {index: Array of new index values}
     */
@@ -872,6 +873,22 @@ export class DataFrame extends Ndframe {
     //         throw Error("Value Error: must specify the column to sort by")
     //     }
 
+    //         sorted_index.map(idx => {
+    //             new_row_data.push(this.values[idx])
+    //         })
+
+    //         if (utils.__key_in_object(kwargs, "inplace") && kwargs['inplace'] == true) {
+    //             this.__update_frame_in_place(new_row_data, null, null, sorted_index, null)
+
+    //         } else {
+    //             let df = new DataFrame(new_row_data, { columns: this.column_names, index: sorted_index, dtype: this.dtypes })
+    //             return df
+    //         }
+
+    //     } else {
+    //         throw Error("Value Error: must specify the column to sort by")
+    //     }
+
     // }
 
 
@@ -1093,17 +1110,14 @@ export class DataFrame extends Ndframe {
     groupby(col) {
 
         let len = this.shape[0]
-
         let column_names = this.column_names
         let col_dict = {};
         let key_column = null;
 
         if (col.length == 2) {
-
             if (column_names.includes(col[0])) {
                 // eslint-disable-next-line no-unused-vars
                 var [data1, col_name1] = indexLoc(this, { "rows": [`0:${len}`], "columns": [`${col[0]}`], "type": "loc" });
-
             }
             else {
                 throw new Error(`column ${col[0]} does not exist`);
@@ -1259,8 +1273,7 @@ export class DataFrame extends Ndframe {
                 let row_value = values[i]
                 for (let j = 0; j < row_value.length; j++) {
 
-                    let val = row_value[j] == 0 ? 0 : !!row_value[j]
-                    if (!val) {
+                    if (isNaN(row_value[j]) && typeof row_value[j] != "string" ) {
                         temp_data.push(nan_val)
                     } else {
                         temp_data.push(row_value[j])
@@ -1269,8 +1282,12 @@ export class DataFrame extends Ndframe {
                 }
                 data.push(temp_data);
             }
+            if (kwargs['inplace']) {
+                this.__update_frame_in_place(data, null, null, null, null)
+            } else {
+                return new DataFrame(data, { columns: columns, index: this.index })
 
-            return new DataFrame(data, { columns: columns, index: this.index })
+            }
 
         }
 
@@ -1306,37 +1323,6 @@ export class DataFrame extends Ndframe {
     }
 
 
-
-    // let new_row_data = []
-    // let row_data = this.values;
-    // let columns = this.column_names;
-
-    // row_data.map(arr=>{
-    //     let temp_arr = []
-    //     arr.map(val=>{
-    //         if (isNaN(val) && typeof val != "string" ){
-    //             temp_arr.push(true)
-    //         }else{
-    //             temp_arr.push(false)
-    //         }
-    //     })
-    //     new_row_data.push(temp_arr)
-    // })
-
-    // // for (let i = 0; i < values.length; i++) {
-    // //     let temp_data = []
-    // //     let row_value = values[i]
-    // //     for (let j = 0; j < row_value.length; j++) {
-
-    // //         let val = row_value[j] == 0 ? true : !row_value[j]
-    // //         temp_data.push(val)
-    // //     }
-    // //     data.push(temp_data);
-    // // }
-
-    // return new DataFrame(new_row_data, { columns: columns, index: this.index })
-
-
     /**
      * Obtain index containing nan values
      * @return Array list (int)

diff --git a/danfojs/src/plotting/plot.js b/danfojs/src/plotting/plot.js
@@ -1,5 +1,5 @@
 //perform plotting
-// import { newPlot } from 'plotly.js' //comment out when building for Node Version
+import { newPlot } from 'plotly.js' //comment out when building for Node Version
 import { Utils } from "../core/utils"
 import { Series } from "../core/series"
 

diff --git a/danfojs/tests/core/frame.js b/danfojs/tests/core/frame.js
@@ -33,6 +33,8 @@ describe("DataFrame", function () {
             df.drop({ columns: ["C"], axis: 1, inplace: true });
             let new_data = [[1, 2], [4, 5]]
             assert.deepEqual(df.values, new_data);
+            assert.deepEqual(df.dtypes.length, 2);
+
         })
 
         it("check if data is updated after row is dropped", function () {
@@ -77,6 +79,7 @@ describe("DataFrame", function () {
             df.drop({ index: ["a", "b"], axis: 0, inplace: true });
             let new_data = [[20, 34, 5]]
             assert.deepEqual(df.values, new_data);
+
         })
     })
 
@@ -1397,8 +1400,8 @@ describe("DataFrame", function () {
             let df = new DataFrame(data, { columns: column })
 
             let df_val = [[-999, 1, 2, 3], [3, 4, -999, 9], [5, 6, 7, 8]]
-
-            assert.deepEqual(df.fillna({ values: -999 }).values, df_val)
+            df.fillna({ values: -999, inplace:true})
+            assert.deepEqual(df.values, df_val)
         });
         it("replace all NaN value", function () {
             let data = [[NaN, 1, 2, 3], [3, 4, NaN, 9], [5, 6, 7, 8]]

diff --git a/package-lock.json b/package-lock.json
diff --git a/package.json b/package.json
@@ -1,6 +1,6 @@
 {
   "name": "danfojs",
-  "version": "0.0.15",
+  "version": "0.1.0",
   "description": "JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.",
   "main": "dist/index.js",
   "contributors": [